update decisiontree regression problem details
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<h3 id="Deploy-to-remote-sites"><a href="#Deploy-to-remote-sites" class="headerlink" title="Deploy to remote sites"></a>Deploy to remote sites</h3><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">$ hexo deploy</span><br></pre></td></tr></table></figure>
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<p>More info: <a target="_blank" rel="noopener" href="https://hexo.io/docs/one-command-deployment.html">Deployment</a></p>
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<li>自助法</li>
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<li>交叉验证法</li>
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</article><div class="post-copyright"><div class="post-copyright__author"><span class="post-copyright-meta"><i class="fas fa-circle-user fa-fw"></i>文章作者: </span><span class="post-copyright-info"><a href="https://rq.shenjianl.cn">shenjianZ</a></span></div><div class="post-copyright__type"><span class="post-copyright-meta"><i class="fas fa-square-arrow-up-right fa-fw"></i>文章链接: </span><span class="post-copyright-info"><a href="https://rq.shenjianl.cn/posts/29139.html">https://rq.shenjianl.cn/posts/29139.html</a></span></div><div class="post-copyright__notice"><span class="post-copyright-meta"><i class="fas fa-circle-exclamation fa-fw"></i>版权声明: </span><span class="post-copyright-info">本博客所有文章除特别声明外，均采用 <a href="https://qr.shenjianl.cn/licenses/by-nc-sa/4.0/" target="_blank">CC BY-NC-SA 4.0</a> 许可协议。转载请注明来自 <a href="https://rq.shenjianl.cn" target="_blank">QuickReference</a>！</span></div></div><div class="tag_share"><div class="post-meta__tag-list"><a class="post-meta__tags" href="/tags/KNN/">KNN</a></div><div class="post_share"><div class="social-share" data-image="/img/avatar.jpg" data-sites="facebook,twitter,wechat,weibo,qq"></div><link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/butterfly-extsrc@1.1.3/sharejs/dist/css/share.min.css" media="print" onload="this.media='all'"><script src="https://cdn.jsdelivr.net/npm/butterfly-extsrc@1.1.3/sharejs/dist/js/social-share.min.js" defer></script></div></div><nav class="pagination-post" id="pagination"><div class="prev-post pull-left"><a href="/posts/12462.html" title="C lang"><div class="cover" style="background: var(--default-bg-color)"></div><div class="pagination-info"><div class="label">上一篇</div><div class="prev_info">C lang</div></div></a></div><div class="next-post pull-right"><a href="/posts/61251.html" title="Hadoop集群Zookeeper配置"><div class="cover" style="background: var(--default-bg-color)"></div><div class="pagination-info"><div class="label">下一篇</div><div class="next_info">Hadoop集群Zookeeper配置</div></div></a></div></nav></div><div class="aside-content" id="aside-content"><div class="card-widget card-info"><div class="is-center"><div class="avatar-img"><img src="/img/avatar.jpg" onerror="this.onerror=null;this.src='/img/friend_404.gif'" alt="avatar"/></div><div class="author-info__name">shenjianZ</div><div class="author-info__description">一份快捷简便的文档，便于查阅编程的细节</div></div><div class="card-info-data site-data is-center"><a href="/archives/"><div class="headline">文章</div><div class="length-num">17</div></a><a href="/tags/"><div class="headline">标签</div><div class="length-num">8</div></a><a href="/categories/"><div class="headline">分类</div><div class="length-num">2</div></a></div><a id="card-info-btn" target="_blank" rel="noopener" href="https://github.com/shenjianz"><i class="fab fa-github"></i><span>Follow Me</span></a><div class="card-info-social-icons is-center"><a class="social-icon" href="https://github.com/shenjianZ" target="_blank" title="Github"><i class="fab fa-github" style="color: #24292e;"></i></a><a class="social-icon" href="mailto:15202078626@163.com" target="_blank" title="Email"><i class="fas fa-envelope" style="color: #4a7dbe;"></i></a></div></div><div class="card-widget card-announcement"><div class="item-headline"><i class="fas fa-bullhorn fa-shake"></i><span>公告</span></div><div class="announcement_content">一个简单快捷的文档知识点查阅网站</div></div><div class="sticky_layout"><div class="card-widget" id="card-toc"><div class="item-headline"><i class="fas fa-stream"></i><span>目录</span><span class="toc-percentage"></span></div><div class="toc-content is-expand"><ol class="toc"><li class="toc-item toc-level-2"><a class="toc-link" href="#k%E8%BF%91%E9%82%BB%E7%AE%97%E6%B3%95%EF%BC%88K-Nearest-Neighbors%EF%BC%89KNN"><span class="toc-number">1.</span> <span class="toc-text">k近邻算法（K-Nearest Neighbors）KNN</span></a><ol class="toc-child"><li class="toc-item toc-level-4"><a class="toc-link" href="#%E8%B7%9D%E7%A6%BB%E5%85%AC%E5%BC%8F-2%E7%BB%B4"><span class="toc-number">1.0.1.</span> <span class="toc-text">距离公式(2维)</span></a></li><li class="toc-item toc-level-4"><a class="toc-link" href="#k%E5%80%BC%E9%80%89%E6%8B%A9%E9%97%AE%E9%A2%98"><span class="toc-number">1.0.2.</span> <span class="toc-text">k值选择问题</span></a></li></ol></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E7%89%B9%E5%BE%81%E9%A2%84%E5%A4%84%E7%90%86"><span class="toc-number">1.1.</span> <span class="toc-text">特征预处理</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#KNN%E4%BB%A3%E7%A0%81%E5%AE%9E%E7%8E%B0"><span class="toc-number">1.2.</span> <span class="toc-text">KNN代码实现</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E4%BA%A4%E5%8F%89%E9%AA%8C%E8%AF%81%E4%B8%8E%E7%BD%91%E6%A0Line truncated
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<figure class="highlight shell"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br></pre></td><td class="code"><pre><span class="line"><span class="meta prompt_">#</span><span class="language-bash">启动zookeeper客户端，并连接zookeeper集群</span></span><br><span class="line">/usr/local/zookeeper/bin/zkCli.sh -server nn1:2181</span><br><span class="line"><span class="meta prompt_"># </span><span class="language-bash">可以简化为:</span></span><br><span class="line">zkCli.sh</span><br></pre></td></tr></table></figure>
|
||||
|
||||
</article><div class="post-copyright"><div class="post-copyright__author"><span class="post-copyright-meta"><i class="fas fa-circle-user fa-fw"></i>文章作者: </span><span class="post-copyright-info"><a href="https://rq.shenjianl.cn">shenjianZ</a></span></div><div class="post-copyright__type"><span class="post-copyright-meta"><i class="fas fa-square-arrow-up-right fa-fw"></i>文章链接: </span><span class="post-copyright-info"><a href="https://rq.shenjianl.cn/posts/61251.html">https://rq.shenjianl.cn/posts/61251.html</a></span></div><div class="post-copyright__notice"><span class="post-copyright-meta"><i class="fas fa-circle-exclamation fa-fw"></i>版权声明: </span><span class="post-copyright-info">本博客所有文章除特别声明外，均采用 <a href="https://qr.shenjianl.cn/licenses/by-nc-sa/4.0/" target="_blank">CC BY-NC-SA 4.0</a> 许可协议。转载请注明来自 <a href="https://rq.shenjianl.cn" target="_blank">QuickReference</a>！</span></div></div><div class="tag_share"><div class="post-meta__tag-list"></div><div class="post_share"><div class="social-share" data-image="/img/avatar.jpg" data-sites="facebook,twitter,wechat,weibo,qq"></div><link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/butterfly-extsrc@1.1.3/sharejs/dist/css/share.min.css" media="print" onload="this.media='all'"><script src="https://cdn.jsdelivr.net/npm/butterfly-extsrc@1.1.3/sharejs/dist/js/social-share.min.js" defer></script></div></div><nav class="pagination-post" id="pagination"><div class="prev-post pull-left"><a href="/posts/29139.html" title="k近邻算法（K-Nearest Neighbors）KNN"><div class="cover" style="background: var(--default-bg-color)"></div><div class="pagination-info"><div class="label">上一篇</div><div class="prev_info">k近邻算法（K-Nearest Neighbors）KNN</div></div></a></div><div class="next-post pull-right"><a href="/posts/61252.html" title="Hadoop集群HDFS配置"><div class="cover" style="background: var(--default-bg-color)"></div><div class="pagination-info"><div class="label">下一篇</div><div class="next_info">Hadoop集群HDFS配置</div></div></a></div></nav></div><div class="aside-content" id="aside-content"><div class="card-widget card-info"><div class="is-center"><div class="avatar-img"><img src="/img/avatar.jpg" onerror="this.onerror=null;this.src='/img/friend_404.gif'" alt="avatar"/></div><div class="author-info__name">shenjianZ</div><div class="author-info__description">一份快捷简便的文档，便于查阅编程的细节</div></div><div class="card-info-data site-data is-center"><a href="/archives/"><div class="headline">文章</div><div class="length-num">17</div></a><a href="/tags/"><div class="headline">标签</div><div class="length-num">8</div></a><a href="/categories/"><div class="headline">分类</div><div class="length-num">2</div></a></div><a id="card-info-btn" target="_blank" rel="noopener" href="https://github.com/shenjianz"><i class="fab fa-github"></i><span>Follow Me</span></a><div class="card-info-social-icons is-center"><a class="social-icon" href="https://github.com/shenjianZ" target="_blank" title="Github"><i class="fab fa-github" style="color: #24292e;"></i></a><a class="social-icon" href="mailto:15202078626@163.com" target="_blank" title="Email"><i class="fas fa-envelope" style="color: #4a7dbe;"></i></a></div></div><div class="card-widget card-announcement"><div class="item-headline"><i class="fas fa-bullhorn fa-shake"></i><span>公告</span></div><div class="announcement_content">一个简单快捷的文档知识点查阅网站</div></div><div class="sticky_layout"><div class="card-widget" id="card-toc"><div class="item-headline"><i class="fas fa-stream"></i><span>目录</span><span class="toc-percentage"></span></div><div class="toc-content is-expand"><ol class="toc"><li class="toc-item toc-level-3"><a class="toc-link" href="#Zookeeper%E8%84%9A%E6%9C%AC%E9%85%8D%E7%BD%AE"><span class="toc-number">1.</span> <span class="toc-text">Zookeeper脚本配置</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#Zookeeper%E5%AE%89%E8%A3%85"><span class="toc-number">2.</span> <span class="toc-text">Zookeeper安装</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#Zookeeper%E9%85%8D%E7%BD%AE"><span class="toc-number">3.</span> <span class="toc-text">Zookeeper配置</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#Zookeeper%E7%9A%84%E5%91%BD%E4%BB%A4"><span class="toc-number">4.</span> <span class="toc-text">Zookeeper的命令</span></a></li></ol></div></div><div class="card-widget card-recent-post"><div class="item-headline"><i class="fas fa-history"></i><span>最新文章</span></div><div class="aside-list"><div class="aside-list-item no-cover"><div class="content"><a class="title" href="/posts/95.html" title="决策树算法">决策树算法</a><time datetime="2025-01-24T04:39:59.000Z" title="发表于 2025-01-24 12:39:59">2025-01-24</time></div></div><div class="aside-lisLine truncated
|
||||
</article><div class="post-copyright"><div class="post-copyright__author"><span class="post-copyright-meta"><i class="fas fa-circle-user fa-fw"></i>文章作者: </span><span class="post-copyright-info"><a href="https://rq.shenjianl.cn">shenjianZ</a></span></div><div class="post-copyright__type"><span class="post-copyright-meta"><i class="fas fa-square-arrow-up-right fa-fw"></i>文章链接: </span><span class="post-copyright-info"><a href="https://rq.shenjianl.cn/posts/61251.html">https://rq.shenjianl.cn/posts/61251.html</a></span></div><div class="post-copyright__notice"><span class="post-copyright-meta"><i class="fas fa-circle-exclamation fa-fw"></i>版权声明: </span><span class="post-copyright-info">本博客所有文章除特别声明外，均采用 <a href="https://qr.shenjianl.cn/licenses/by-nc-sa/4.0/" target="_blank">CC BY-NC-SA 4.0</a> 许可协议。转载请注明来自 <a href="https://rq.shenjianl.cn" target="_blank">QuickReference</a>！</span></div></div><div class="tag_share"><div class="post-meta__tag-list"></div><div class="post_share"><div class="social-share" data-image="/img/avatar.jpg" data-sites="facebook,twitter,wechat,weibo,qq"></div><link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/butterfly-extsrc@1.1.3/sharejs/dist/css/share.min.css" media="print" onload="this.media='all'"><script src="https://cdn.jsdelivr.net/npm/butterfly-extsrc@1.1.3/sharejs/dist/js/social-share.min.js" defer></script></div></div><nav class="pagination-post" id="pagination"><div class="prev-post pull-left"><a href="/posts/61253.html" title="Hadoop集群搭建基础环境"><div class="cover" style="background: var(--default-bg-color)"></div><div class="pagination-info"><div class="label">上一篇</div><div class="prev_info">Hadoop集群搭建基础环境</div></div></a></div><div class="next-post pull-right"><a href="/posts/61252.html" title="Hadoop集群HDFS配置"><div class="cover" style="background: var(--default-bg-color)"></div><div class="pagination-info"><div class="label">下一篇</div><div class="next_info">Hadoop集群HDFS配置</div></div></a></div></nav></div><div class="aside-content" id="aside-content"><div class="card-widget card-info"><div class="is-center"><div class="avatar-img"><img src="/img/avatar.jpg" onerror="this.onerror=null;this.src='/img/friend_404.gif'" alt="avatar"/></div><div class="author-info__name">shenjianZ</div><div class="author-info__description">一份快捷简便的文档，便于查阅编程的细节</div></div><div class="card-info-data site-data is-center"><a href="/archives/"><div class="headline">文章</div><div class="length-num">17</div></a><a href="/tags/"><div class="headline">标签</div><div class="length-num">8</div></a><a href="/categories/"><div class="headline">分类</div><div class="length-num">2</div></a></div><a id="card-info-btn" target="_blank" rel="noopener" href="https://github.com/shenjianz"><i class="fab fa-github"></i><span>Follow Me</span></a><div class="card-info-social-icons is-center"><a class="social-icon" href="https://github.com/shenjianZ" target="_blank" title="Github"><i class="fab fa-github" style="color: #24292e;"></i></a><a class="social-icon" href="mailto:15202078626@163.com" target="_blank" title="Email"><i class="fas fa-envelope" style="color: #4a7dbe;"></i></a></div></div><div class="card-widget card-announcement"><div class="item-headline"><i class="fas fa-bullhorn fa-shake"></i><span>公告</span></div><div class="announcement_content">一个简单快捷的文档知识点查阅网站</div></div><div class="sticky_layout"><div class="card-widget" id="card-toc"><div class="item-headline"><i class="fas fa-stream"></i><span>目录</span><span class="toc-percentage"></span></div><div class="toc-content is-expand"><ol class="toc"><li class="toc-item toc-level-3"><a class="toc-link" href="#Zookeeper%E8%84%9A%E6%9C%AC%E9%85%8D%E7%BD%AE"><span class="toc-number">1.</span> <span class="toc-text">Zookeeper脚本配置</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#Zookeeper%E5%AE%89%E8%A3%85"><span class="toc-number">2.</span> <span class="toc-text">Zookeeper安装</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#Zookeeper%E9%85%8D%E7%BD%AE"><span class="toc-number">3.</span> <span class="toc-text">Zookeeper配置</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#Zookeeper%E7%9A%84%E5%91%BD%E4%BB%A4"><span class="toc-number">4.</span> <span class="toc-text">Zookeeper的命令</span></a></li></ol></div></div><div class="card-widget card-recent-post"><div class="item-headline"><i class="fas fa-history"></i><span>最新文章</span></div><div class="aside-list"><div class="aside-list-item no-cover"><div class="content"><a class="title" href="/posts/95.html" title="决策树算法">决策树算法</a><time datetime="2025-01-24T04:39:59.000Z" title="发表于 2025-01-24 12:39:59">2025-01-24</time></div></div><div class="aside-list-item no-cover"><div Line truncated
|
||||
POWERMODE.shake = true;
|
||||
POWERMODE.mobile = false;
|
||||
document.body.addEventListener('input', POWERMODE);
|
||||
|
||||
@@ -195,7 +195,7 @@
|
||||
<li><p>启动datanode节点，在s1、s2、s3执行</p>
|
||||
<figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment">#启动各个节点的datanode</span></span><br><span class="line">hadoop-daemons.sh start datanode</span><br></pre></td></tr></table></figure></li>
|
||||
</ul>
|
||||
<h3 id="集群启动"><a href="#集群启动" class="headerlink" title="集群启动"></a>集群启动</h3><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">start-dfs.sh</span><br></pre></td></tr></table></figure></article><div class="post-copyright"><div class="post-copyright__author"><span class="post-copyright-meta"><i class="fas fa-circle-user fa-fw"></i>文章作者: </span><span class="post-copyright-info"><a href="https://rq.shenjianl.cn">shenjianZ</a></span></div><div class="post-copyright__type"><span class="post-copyright-meta"><i class="fas fa-square-arrow-up-right fa-fw"></i>文章链接: </span><span class="post-copyright-info"><a href="https://rq.shenjianl.cn/posts/61252.html">https://rq.shenjianl.cn/posts/61252.html</a></span></div><div class="post-copyright__notice"><span class="post-copyright-meta"><i class="fas fa-circle-exclamation fa-fw"></i>版权声明: </span><span class="post-copyright-info">本博客所有文章除特别声明外，均采用 <a href="https://qr.shenjianl.cn/licenses/by-nc-sa/4.0/" target="_blank">CC BY-NC-SA 4.0</a> 许可协议。转载请注明来自 <a href="https://rq.shenjianl.cn" target="_blank">QuickReference</a>！</span></div></div><div class="tag_share"><div class="post-meta__tag-list"></div><div class="post_share"><div class="social-share" data-image="/img/avatar.jpg" data-sites="facebook,twitter,wechat,weibo,qq"></div><link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/butterfly-extsrc@1.1.3/sharejs/dist/css/share.min.css" media="print" onload="this.media='all'"><script src="https://cdn.jsdelivr.net/npm/butterfly-extsrc@1.1.3/sharejs/dist/js/social-share.min.js" defer></script></div></div><nav class="pagination-post" id="pagination"><div class="prev-post pull-left"><a href="/posts/61251.html" title="Hadoop集群Zookeeper配置"><div class="cover" style="background: var(--default-bg-color)"></div><div class="pagination-info"><div class="label">上一篇</div><div class="prev_info">Hadoop集群Zookeeper配置</div></div></a></div><div class="next-post pull-right"><a href="/posts/61253.html" title="Hadoop集群搭建基础环境"><div class="cover" style="background: var(--default-bg-color)"></div><div class="pagination-info"><div class="label">下一篇</div><div class="next_info">Hadoop集群搭建基础环境</div></div></a></div></nav></div><div class="aside-content" id="aside-content"><div class="card-widget card-info"><div class="is-center"><div class="avatar-img"><img src="/img/avatar.jpg" onerror="this.onerror=null;this.src='/img/friend_404.gif'" alt="avatar"/></div><div class="author-info__name">shenjianZ</div><div class="author-info__description">一份快捷简便的文档，便于查阅编程的细节</div></div><div class="card-info-data site-data is-center"><a href="/archives/"><div class="headline">文章</div><div class="length-num">17</div></a><a href="/tags/"><div class="headline">标签</div><div class="length-num">8</div></a><a href="/categories/"><div class="headline">分类</div><div class="length-num">2</div></a></div><a id="card-info-btn" target="_blank" rel="noopener" href="https://github.com/shenjianz"><i class="fab fa-github"></i><span>Follow Me</span></a><div class="card-info-social-icons is-center"><a class="social-icon" href="https://github.com/shenjianZ" target="_blank" title="Github"><i class="fab fa-github" style="color: #24292e;"></i></a><a class="social-icon" href="mailto:15202078626@163.com" target="_blank" title="Email"><i class="fas fa-envelope" style="color: #4a7dbe;"></i></a></div></div><div class="card-widget card-announcement"><div class="item-headline"><i class="fas fa-bullhorn fa-shake"></i><span>公告</span></div><div class="announcement_content">一个简单快捷的文档知识点查阅网站</div></div><div class="sticky_layout"><div class="card-widget" id="card-toc"><div class="item-headline"><i class="fas fa-stream"></i><span>目录</span><span class="toc-percentage"></span></div><div class="toc-content is-expand"><ol class="toc"><li class="toc-item toc-level-3"><a class="toc-link" href="#%E4%B8%8A%E4%BC%A0hadoop-3-1-4-tar-gz%E5%88%B0-tmp%EF%BC%8C%E8%A7%A3%E5%8E%8B"><span class="toc-number">1.</span> <span class="toc-text">上传hadoop-3.1.4.tar.gz到/tmp，解压</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E9%85%8D%E7%BD%AE%E7%8E%AF%E5%A2%83%E5%8F%98%E9%87%8F"><span class="toc-number">2.</span> <span class="toc-text">配置环境变量</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E4%BF%AE%E6%94%B9core-site-xml"><span class="toc-number">3.</span> <span class="toc-text">修改core-site.xml</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E4%BF%AE%E6%94%B9hdfs-site-xml"><span class="toc-number">4.</span> <span class="toc-text">修改hdfs-site.xml</span></a></li><li class="toc-item toc-level-3"><a class="toc-linkLine truncated
|
||||
<h3 id="集群启动"><a href="#集群启动" class="headerlink" title="集群启动"></a>集群启动</h3><figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">start-dfs.sh</span><br></pre></td></tr></table></figure></article><div class="post-copyright"><div class="post-copyright__author"><span class="post-copyright-meta"><i class="fas fa-circle-user fa-fw"></i>文章作者: </span><span class="post-copyright-info"><a href="https://rq.shenjianl.cn">shenjianZ</a></span></div><div class="post-copyright__type"><span class="post-copyright-meta"><i class="fas fa-square-arrow-up-right fa-fw"></i>文章链接: </span><span class="post-copyright-info"><a href="https://rq.shenjianl.cn/posts/61252.html">https://rq.shenjianl.cn/posts/61252.html</a></span></div><div class="post-copyright__notice"><span class="post-copyright-meta"><i class="fas fa-circle-exclamation fa-fw"></i>版权声明: </span><span class="post-copyright-info">本博客所有文章除特别声明外，均采用 <a href="https://qr.shenjianl.cn/licenses/by-nc-sa/4.0/" target="_blank">CC BY-NC-SA 4.0</a> 许可协议。转载请注明来自 <a href="https://rq.shenjianl.cn" target="_blank">QuickReference</a>！</span></div></div><div class="tag_share"><div class="post-meta__tag-list"></div><div class="post_share"><div class="social-share" data-image="/img/avatar.jpg" data-sites="facebook,twitter,wechat,weibo,qq"></div><link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/butterfly-extsrc@1.1.3/sharejs/dist/css/share.min.css" media="print" onload="this.media='all'"><script src="https://cdn.jsdelivr.net/npm/butterfly-extsrc@1.1.3/sharejs/dist/js/social-share.min.js" defer></script></div></div><nav class="pagination-post" id="pagination"><div class="prev-post pull-left"><a href="/posts/61251.html" title="Hadoop集群Zookeeper配置"><div class="cover" style="background: var(--default-bg-color)"></div><div class="pagination-info"><div class="label">上一篇</div><div class="prev_info">Hadoop集群Zookeeper配置</div></div></a></div><div class="next-post pull-right"><a href="/posts/16107.html" title="Hello World"><div class="cover" style="background: var(--default-bg-color)"></div><div class="pagination-info"><div class="label">下一篇</div><div class="next_info">Hello World</div></div></a></div></nav></div><div class="aside-content" id="aside-content"><div class="card-widget card-info"><div class="is-center"><div class="avatar-img"><img src="/img/avatar.jpg" onerror="this.onerror=null;this.src='/img/friend_404.gif'" alt="avatar"/></div><div class="author-info__name">shenjianZ</div><div class="author-info__description">一份快捷简便的文档，便于查阅编程的细节</div></div><div class="card-info-data site-data is-center"><a href="/archives/"><div class="headline">文章</div><div class="length-num">17</div></a><a href="/tags/"><div class="headline">标签</div><div class="length-num">8</div></a><a href="/categories/"><div class="headline">分类</div><div class="length-num">2</div></a></div><a id="card-info-btn" target="_blank" rel="noopener" href="https://github.com/shenjianz"><i class="fab fa-github"></i><span>Follow Me</span></a><div class="card-info-social-icons is-center"><a class="social-icon" href="https://github.com/shenjianZ" target="_blank" title="Github"><i class="fab fa-github" style="color: #24292e;"></i></a><a class="social-icon" href="mailto:15202078626@163.com" target="_blank" title="Email"><i class="fas fa-envelope" style="color: #4a7dbe;"></i></a></div></div><div class="card-widget card-announcement"><div class="item-headline"><i class="fas fa-bullhorn fa-shake"></i><span>公告</span></div><div class="announcement_content">一个简单快捷的文档知识点查阅网站</div></div><div class="sticky_layout"><div class="card-widget" id="card-toc"><div class="item-headline"><i class="fas fa-stream"></i><span>目录</span><span class="toc-percentage"></span></div><div class="toc-content is-expand"><ol class="toc"><li class="toc-item toc-level-3"><a class="toc-link" href="#%E4%B8%8A%E4%BC%A0hadoop-3-1-4-tar-gz%E5%88%B0-tmp%EF%BC%8C%E8%A7%A3%E5%8E%8B"><span class="toc-number">1.</span> <span class="toc-text">上传hadoop-3.1.4.tar.gz到/tmp，解压</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E9%85%8D%E7%BD%AE%E7%8E%AF%E5%A2%83%E5%8F%98%E9%87%8F"><span class="toc-number">2.</span> <span class="toc-text">配置环境变量</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E4%BF%AE%E6%94%B9core-site-xml"><span class="toc-number">3.</span> <span class="toc-text">修改core-site.xml</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E4%BF%AE%E6%94%B9hdfs-site-xml"><span class="toc-number">4.</span> <span class="toc-text">修改hdfs-site.xml</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E4%BF%AE%E6%94%B9hadoop-env-Line truncated
|
||||
POWERMODE.shake = true;
|
||||
POWERMODE.mobile = false;
|
||||
document.body.addEventListener('input', POWERMODE);
|
||||
|
||||
@@ -208,7 +208,7 @@
|
||||
<li><p>将 <code>/home/hadoop/bin</code>添加到hadoop用户的环境变量，需要切换到<code>hadoop</code>用户</p>
|
||||
<figure class="highlight bash"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><span class="line"><span class="built_in">echo</span> <span class="string">'export PATH=$PATH:/home/hadoop/bin'</span> >> ~/.bashrc && <span class="built_in">source</span> ~/.bashrc</span><br><span class="line">scp_all.sh /home/hadoop/.bashrc /home/hadoop/</span><br><span class="line">ssh_all.sh <span class="built_in">source</span> ~/.bashrc </span><br></pre></td></tr></table></figure></li>
|
||||
</ul>
|
||||
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})(window)</script><meta name="generator" content="Hexo 7.3.0"></head><body><div id="web_bg"></div><div id="sidebar"><div id="menu-mask"></div><div id="sidebar-menus"><div class="avatar-img is-center"><img src="/img/avatar.jpg" onerror="onerror=null;src='/img/friend_404.gif'" alt="avatar"/></div><div class="sidebar-site-data site-data is-center"><a href="/archives/"><div class="headline">文章</div><div class="length-num">17</div></a><a href="/tags/"><div class="headline">标签</div><div class="length-num">8</div></a><a href="/categories/"><div class="headline">分类</div><div class="length-num">2</div></a></div><hr class="custom-hr"/><div class="menus_items"><div class="menus_item"><a class="site-page" href="/"><i class="fa-fw fas fa-home"></i><span> Home</span></a></div><div class="menus_item"><a class="site-page" href="/archives/"><i class="fa-fw fas fa-archive"></i><span> Archives</span></a></div><div class="menus_item"><a class="site-page" href="/tags/"><i class="fa-fw fas fa-tags"></i><span> Tags</span></a></div><div class="menus_item"><a class="site-page" href="/categories/"><i class="fa-fw fas fa-folder-open"></i><span> Categories</span></a></div><div class="menus_item"><a class="site-page group" href="javascript:void(0);"><i class="fa-fw fas fa-list"></i><span> List</span><i class="fas fa-chevron-down"></i></a><ul class="menus_item_child"><li><a class="site-page child" href="/music/"><i class="fa-fw fas fa-music"></i><span> Music</span></a></li><li><a class="site-page child" href="/movies/"><i class="fa-fw fas fa-video"></i><span> Movie</span></a></li></ul></div><div class="menus_item"><a class="site-page" href="/link/"><i class="fa-fw fas fa-link"></i><span> Link</span></a></div><div class="menus_item"><a class="site-page" href="/about/"><i class="fa-fw fas fa-heart"></i><span> About</span></a></div></div></div></div><div class="post" id="body-wrap"><header class="post-bg fixed" id="page-header" style="background-image: url('/img/site01.jpg')"><nav id="nav"><span id="blog-info"><a href="/" title="QuickReference"><span class="site-name">QuickReference</span></a></span><div id="menus"><div id="search-button"><a class="site-page social-icon search" href="javascript:void(0);"><i class="fas fa-search fa-fw"></i><span> 搜索</span></a></div><div class="menus_items"><div class="menus_item"><a class="site-page" href="/"><i class="fa-fw fas fa-home"></i><span> Home</span></a></div><div class="menus_item"><a class="site-page" href="/archives/"><i class="fa-fw fas fa-archive"></i><span> Archives</span></a></div><div class="menus_item"><a class="site-page" href="/tags/"><i class="fa-fw fas fa-tags"></i><span> Tags</span></a></div><div class="menus_item"><a class="site-page" href="/categories/"><i class="fa-fw fas fa-folder-open"></i><span> Categories</span></a></div><div class="menus_item"><a class="site-page group" href="javascript:void(0);"><i class="fa-fw fas fa-list"></i><span> List</span><i class="fas fa-chevron-down"></i></a><ul class="menus_item_child"><li><a class="site-page child" href="/music/"><i class="fa-fw fas fa-music"></i><span> Music</span></a></li><li><a class="site-page child" href="/movies/"><i class="fa-fw fas fa-video"></i><span> Movie</span></a></li></ul></div><div class="menus_item"><a class="site-page" href="/link/"><i class="fa-fw fas fa-link"></i><span> Link</span></a></div><div class="menus_item"><a class="site-page" href="/about/"><i class="fa-fw fas fa-heart"></i><span> About</span></a></div></div><div id="toggle-menu"><a class="site-page" href="javascript:void(0);"><i class="fas fa-bars fa-fw"></i></a></div></div></nav><div id="post-info"><h1 class="post-title">决策树算法</h1><div id="post-meta"><div class="meta-firstline"><span class="post-meta-date"><i class="far fa-calendar-alt fa-fw post-meta-icon"></i><span class="post-meta-label">发表于</span><time class="post-meta-date-created" datetime="2025-01-24T04:39:59.000Z" title="发表于 2025-01-24 12:39:59">2025-01-24</time><span class="post-meta-separator">|</span><i class="fas fa-history fa-fw post-meta-icon"></i><span class="post-meta-label">更新于</span><time class="post-meta-date-updated" datetime="2025-01-24T10:19:27.766Z" title="更新于 2025-01-24 18:19:27">2025-01-24</time></span><span class="post-meta-categories"><span class="post-meta-separator">|</span><i class="fas fa-inbox fa-fw post-meta-icon"></i><a class="post-meta-categories" href="/categories/machinelearning/">machinelearning</a></span></div><div class="meta-secondline"><span class="post-meta-separator">|</span><span class="post-meta-pv-cv" id="" data-flag-title="决策树算法"><i class="far fa-eye fa-fw post-meta-icon"></i><span class="post-meta-label">阅读量:</span><span id="busuanzi_value_page_pv"><i class="fa-solid fa-spinner fa-spin"></i></span></span></div></div></div></header><main class="layout" id="content-inner"><div id="post"><article class="post-content" id="article-container"><h3 id="C4-5"><a href="#C4-5" class="headerlinLine truncated
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<h3 id="ID3"><a href="#ID3" class="headerlink" title="ID3"></a>ID3</h3><p>D3 是一种基于信息增益（Information Gain）的决策树算法</p>
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<h3 id="Cart"><a href="#Cart" class="headerlink" title="Cart"></a>Cart</h3><p>CART（分类与回归树）一种决策树算法，，CART 使用 <strong>二叉树结构</strong>，即每个节点只能有两个子节点。</p>
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<h3 id="cart剪枝"><a href="#cart剪枝" class="headerlink" title="cart剪枝"></a>cart剪枝</h3><p>CART 决策树的剪枝方法分为 <strong>预剪枝</strong>（Pre-pruning）和 <strong>后剪枝</strong>（Post-pruning）两种：</p>
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@@ -179,30 +179,14 @@
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<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># tfi-df</span></span><br><span class="line"><span class="keyword">from</span> sklearn.feature_extraction.text <span class="keyword">import</span> TfidfVectorizer</span><br><span class="line"><span class="keyword">import</span> jieba</span><br><span class="line">data=[<span class="string">"一种还是一种今天很残酷，明天更残酷，后天很美好，但绝对大部分是死在明天晚上，所以每个人不要放弃今天。"</span>,</span><br><span class="line"> <span class="string">"我们看到的从很远星系来的光是在几百万年之前发出的，这样当我们看到宇宙时，我们是在看它的过去"</span>,</span><br><span class="line"> <span class="string">"如果只用一种方式了解某样事物，你就不会真正了解它。了解事物真正含义的秘密取决于如何将其与我们所了解的事物相联系"</span>]</span><br><span class="line"><span class="built_in">list</span> = []</span><br><span class="line"><span class="keyword">for</span> item <span class="keyword">in</span> data:</span><br><span class="line"> <span class="built_in">list</span>.append(<span class="string">" "</span>.join(jieba.cut(item)))</span><br><span class="line">transfer = TfidfVectorizer()</span><br><span class="line">new_data = transfer.fit_transform(<span class="built_in">list</span>)</span><br><span class="line"><span class="built_in">print</span>(<span class="string">f"特征名字：\n<span class="subst">{transfer.get_feature_names_out()}</span>"</span>)</span><br><span class="line"></span><br><span class="line"><span class="built_in">print</span>(<span class="string">f"转换后的特征矩阵:\n<span class="subst">{ new_data.toarray()}</span>"</span>)</span><br><span class="line"><span class="built_in">print</span>(<span class="string">f"转换后的数据:\n<span class="subst">{new_data}</span>"</span>)</span><br></pre></td></tr></table></figure>
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<h3 id="回归决策树"><a href="#回归决策树" class="headerlink" title="回归决策树"></a>回归决策树</h3><p><<<<<<< HEAD</p>
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<h4 id="决策树算法的应用-（泰坦尼克号沉船幸存者预测）"><a href="#决策树算法的应用-（泰坦尼克号沉船幸存者预测）" class="headerlink" title="决策树算法的应用 （泰坦尼克号沉船幸存者预测）"></a>决策树算法的应用 （泰坦尼克号沉船幸存者预测）</h4><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> seaborn <span class="keyword">as</span> sns</span><br><span class="line"><span class="keyword">import</span> pandas <span class="keyword">as</span> pd</span><br><span class="line"><span class="keyword">import</span> numpy <span class="keyword">as</span> np</span><br><span class="line"><span class="keyword">from</span> sklearn.model_selection <span class="keyword">import</span> train_test_split</span><br><span class="line"><span class="keyword">from</span> sklearn.feature_extraction <span class="keyword">import</span> DictVectorizer</span><br><span class="line"><span class="keyword">from</span> sklearn.tree <span class="keyword">import</span> DecisionTreeClassifier,export_graphviz</span><br><span class="line"><span class="comment"># 1.获取数据集 - 加载 Titanic 数据集</span></span><br><span class="line">titanic = sns.load_dataset(<span class="string">'titanic'</span>)</span><br><span class="line">missing_age_count = titanic[<span class="string">'age'</span>].isna().<span class="built_in">sum</span>()</span><br><span class="line"><span class="comment"># print(f"缺失的 age 数量: {missing_age_count}")</span></span><br><span class="line"><span class="comment"># 2. 数据基本处理</span></span><br><span class="line"><span class="comment"># 2.1 确认特征值、目标值</span></span><br><span class="line">X = titanic[[<span class="string">'pclass'</span>,<span class="string">'age'</span>,<span class="string">'sex'</span>]]</span><br><span class="line">y = titanic[<span class="string">'survived'</span>]</span><br><span class="line"><span class="comment"># 2.2 缺失值处理</span></span><br><span class="line">X.loc[:, <span class="string">'age'</span>] = X[<span class="string">'age'</span>].fillna(value=X[<span class="string">'age'</span>].mean()) <span class="comment"># 使用 .loc 进行修改</span></span><br><span class="line"><span class="comment"># 2.3 划分数据集</span></span><br><span class="line">X_train,X_test,y_train,y_test = train_test_split(X,y,random_state=<span class="number">22</span>)</span><br><span class="line"><span class="comment"># 3. 特征工程（字典特征提取）</span></span><br><span class="line">X_train = X_train.to_dict(orient=<span class="string">"records"</span>)</span><br><span class="line">X_test= X_test.to_dict(orient=<span class="string">"records"</span>)</span><br><span class="line">transfer = DictVectorizer()</span><br><span class="line">X_train = transfer.fit_transform(X_train)</span><br><span class="line">X_test = transfer.transform(X_test)</span><br><span class="line"><span class="comment"># 4. 机器学习 决策树算法</span></span><br><span class="line">estimator = DecisionTreeClassifier(criterion=<span class="string">"gini"</span>)</span><br><span class="line">estimator.fit(X_train,y_train)</span><br><span class="line">y_pred = estimator.predict(X_test)</span><br><span class="line"><span class="built_in">print</span>(<span class="string">f"模型的测试集的预测值：<span class="subst">{y_pred}</span>"</span>)</span><br><span class="line">ret = estimator.score(X_test,y_test)</span><br><span class="line"><span class="built_in">print</span>(<span class="string">f"模型的评分:<span class="subst">{ret}</span>"</span>)</span><br><span class="line"><span class="built_in">print</span>(X_testLine truncated
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<h3 id="回归决策树"><a href="#回归决策树" class="headerlink" title="回归决策树"></a>回归决策树</h3><h4 id="决策树算法的应用-（泰坦尼克号沉船幸存者预测）"><a href="#决策树算法的应用-（泰坦尼克号沉船幸存者预测）" class="headerlink" title="决策树算法的应用 （泰坦尼克号沉船幸存者预测）"></a>决策树算法的应用 （泰坦尼克号沉船幸存者预测）</h4><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> seaborn <span class="keyword">as</span> sns</span><br><span class="line"><span class="keyword">import</span> pandas <span class="keyword">as</span> pd</span><br><span class="line"><span class="keyword">import</span> numpy <span class="keyword">as</span> np</span><br><span class="line"><span class="keyword">from</span> sklearn.model_selection <span class="keyword">import</span> train_test_split</span><br><span class="line"><span class="keyword">from</span> sklearn.feature_extraction <span class="keyword">import</span> DictVectorizer</span><br><span class="line"><span class="keyword">from</span> sklearn.tree <span class="keyword">import</span> DecisionTreeClassifier,export_graphviz</span><br><span class="line"><span class="comment"># 1.获取数据集 - 加载 Titanic 数据集</span></span><br><span class="line">titanic = sns.load_dataset(<span class="string">'titanic'</span>)</span><br><span class="line">missing_age_count = titanic[<span class="string">'age'</span>].isna().<span class="built_in">sum</span>()</span><br><span class="line"><span class="comment"># print(f"缺失的 age 数量: {missing_age_count}")</span></span><br><span class="line"><span class="comment"># 2. 数据基本处理</span></span><br><span class="line"><span class="comment"># 2.1 确认特征值、目标值</span></span><br><span class="line">X = titanic[[<span class="string">'pclass'</span>,<span class="string">'age'</span>,<span class="string">'sex'</span>]]</span><br><span class="line">y = titanic[<span class="string">'survived'</span>]</span><br><span class="line"><span class="comment"># 2.2 缺失值处理</span></span><br><span class="line">X.loc[:, <span class="string">'age'</span>] = X[<span class="string">'age'</span>].fillna(value=X[<span class="string">'age'</span>].mean()) <span class="comment"># 使用 .loc 进行修改</span></span><br><span class="line"><span class="comment"># 2.3 划分数据集</span></span><br><span class="line">X_train,X_test,y_train,y_test = train_test_split(X,y,random_state=<span class="number">22</span>)</span><br><span class="line"><span class="comment"># 3. 特征工程（字典特征提取）</span></span><br><span class="line">X_train = X_train.to_dict(orient=<span class="string">"records"</span>)</span><br><span class="line">X_test= X_test.to_dict(orient=<span class="string">"records"</span>)</span><br><span class="line">transfer = DictVectorizer()</span><br><span class="line">X_train = transfer.fit_transform(X_train)</span><br><span class="line">X_test = transfer.transform(X_test)</span><br><span class="line"><span class="comment"># 4. 机器学习 决策树算法</span></span><br><span class="line">estimator = DecisionTreeClassifier(criterion=<span class="string">"gini"</span>)</span><br><span class="line">estimator.fit(X_train,y_train)</span><br><span class="line">y_pred = estimator.predict(X_test)</span><br><span class="line"><span class="built_in">print</span>(<span class="string">f"模型的测试集的预测值：<span class="subst">{y_pred}</span>"</span>)</span><br><span class="line">ret = estimator.score(X_test,y_test)</span><br><span class="line"><span class="built_in">print</span>(<span class="string">f"模型的评分:<span claLine truncated
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<p>生成对应的图</p>
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<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">from</span> sklearn.tree <span class="keyword">import</span> export_graphviz</span><br><span class="line"><span class="keyword">import</span> graphviz <span class="comment"># 用于渲染图像</span></span><br><span class="line"></span><br><span class="line"><span class="comment"># 导出决策树的 Graphviz 表示</span></span><br><span class="line">export_graphviz(estimator, out_file=<span class="string">'./data/tree.dot'</span>, </span><br><span class="line"> feature_names=transfer.get_feature_names_out()) <span class="comment"># 特征名称</span></span><br><span class="line"><span class="comment"># 使用 graphviz 渲染 .dot 文件</span></span><br><span class="line"><span class="keyword">with</span> <span class="built_in">open</span>(<span class="string">'./data/tree.dot'</span>, <span class="string">'r'</span>) <span class="keyword">as</span> f:</span><br><span class="line"> dot_graph = f.read()</span><br><span class="line"><span class="comment"># 渲染决策树</span></span><br><span class="line">graph = graphviz.Source(dot_graph)</span><br><span class="line"></span><br><span class="line"><span class="comment"># 设置保存路径</span></span><br><span class="line">output_path = <span class="string">'./data/decision_tree'</span> <span class="comment"># 自定义保存路径</span></span><br><span class="line"></span><br><span class="line"><span class="comment"># 保存图像到指定路径，格式可以是 .png, .pdf, .jpg 等</span></span><br><span class="line"><span class="comment"># graph.render(output_path, format='png') # 保存为 .png 文件</span></span><br><span class="line"></span><br><span class="line"><span class="comment"># 显示图像</span></span><br><span class="line">graph.view(output_path) <span class="comment"># 打开图像，path为保存路径，不需要加后缀</span></span><br><span class="line"></span><br></pre></td></tr></table></figure>
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<h1 id="Webgraphviz，这个网站可以将tree-dot文件的内容生成对应的可视化树"><a href="#Webgraphviz，这个网站可以将tree-dot文件的内容生成对应的可视化树" class="headerlink" title="Webgraphviz，这个网站可以将tree.dot文件的内容生成对应的可视化树"></a><a target="_blank" rel="noopener" href="http://webgraphviz.com/">Webgraphviz</a>，这个网站可以将<code>tree.dot</code>文件的内容生成对应的可视化树</h1><p><a target="_blank" rel="noopener" href="http://webgraphviz.com/">Webgraphviz</a></p>
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<blockquote>
|
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<blockquote>
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<blockquote>
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<blockquote>
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<blockquote>
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<blockquote>
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<blockquote>
|
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<p>efff4fc1310b4d2f201748d9b976f5efbb4a42bf</p>
|
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</blockquote>
|
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</blockquote>
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</blockquote>
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</blockquote>
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</blockquote>
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</blockquote>
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</blockquote>
|
||||
<p><a target="_blank" rel="noopener" href="http://webgraphviz.com/">Webgraphviz</a>，这个网站可以将<code>tree.dot</code>文件的内容生成对应的可视化树</p>
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<figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br><span class="line">26</span><br><span class="line">27</span><br><span class="line">28</span><br><span class="line">29</span><br><span class="line">30</span><br><span class="line">31</span><br><span class="line">32</span><br><span class="line">33</span><br><span class="line">34</span><br><span class="line">35</span><br><span class="line">36</span><br><span class="line">37</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> numpy <span class="keyword">as</span> np</span><br><span class="line"><span class="keyword">import</span> matplotlib.pyplot <span class="keyword">as</span> plt</span><br><span class="line"><span class="keyword">from</span> sklearn.linear_model <span class="keyword">import</span> LinearRegression</span><br><span class="line"><span class="keyword">from</span> sklearn.tree <span class="keyword">import</span> DecisionTreeRegressor</span><br><span class="line"><span class="keyword">from</span> matplotlib <span class="keyword">import</span> rcParams</span><br><span class="line"></span><br><span class="line"><span class="comment"># 设置matplotlib使用的字体为SimHei（黑体）</span></span><br><span class="line">rcParams[<span class="string">'font.sans-serif'</span>] = [<span class="string">'SimHei'</span>] <span class="comment"># 也可以使用 'Microsoft YaHei'</span></span><br><span class="line">rcParams[<span class="string">'axes.unicode_minus'</span>] = <span class="literal">False</span> <span class="comment"># 正常显示负号</span></span><br><span class="line">x = np.array(<span class="built_in">list</span>(<span class="built_in">range</span>(<span class="number">1</span>,<span class="number">11</span>))).reshape(-<span class="number">1</span>,<span class="number">1</span>)</span><br><span class="line">y = ([<span class="number">5.56</span>,<span class="number">5.70</span>,<span class="number">5.91</span>,<span class="number">6.40</span>,<span class="number">6.80</span>,<span class="number">7.05</span>,<span class="number">8.90</span>,<span class="number">8.70</span>,<span class="number">9.00</span>,<span class="number">9.05</span>])</span><br><span class="line"></span><br><span class="line">m1 = DecisionTreeRegressor(max_depth=<span class="number">1</span>)</span><br><span class="line">m2 = DecisionTreeRegressor(max_depth=<span class="number">3</span>)</span><br><span class="line">m3 = DecisionTreeRegressor()</span><br><span class="line"></span><br><span class="line"><span class="comment"># 模型训练</span></span><br><span class="line">m1.fit(x,y)</span><br><span class="line">m2.fit(x,y)</span><br><span class="line">m3.fit(x,y)</span><br><span class="line"></span><br><span class="line"><span class="comment"># 模型预测</span></span><br><span class="line">x_test = np.arange(<span class="number">0</span>,<span class="number">10</span>,<span class="number">0.01</span>).reshape(-<span class="number">1</span>,<span class="number">1</span>)</span><br><span class="line">y_1 = m1.predict(x_test)</span><br><span class="line">y_2 = m2.predict(x_test)</span><br><span class="line">y_3 = m3.predict(x_test)</span><br><span class="line"></span><br><span class="line"><span class="comment"># 结果展示</span></span><br><span class="line">plt.figure(figsize=(<span class="number">10</span>,<span class="number">6</span>),dpi=<span class="number">100</span>)</span><br><span class="line">plt.scatter(x,y ,label = <span class="string">"data"</span>)</span><br><span class="line">plt.plot(x_test,y_1,label = <span class="string">"max_depth=1"</span>)</span><br><span class="line">plt.plot(x_test,y_2,label = <span class="string">"max_depth=3"</span>)</span><br><span class="line">plt.plot(x_test,y_3,label = <span class="string">"linearregression"</span>)</span><br><span class="line">plt.xlabel(<span class="string">"数据"</span>)</span><br><span class="line">plt.ylabel(<span class="string">"预测值"</span>)</span><br><span class="line">plt.legend()</span><br><span class="line">plt.show()</span><br></pre></tdLine truncated
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</article><div class="post-copyright"><div class="post-copyright__author"><span class="post-copyright-meta"><i class="fas fa-circle-user fa-fw"></i>文章作者: </span><span class="post-copyright-info"><a href="https://rq.shenjianl.cn">shenjianZ</a></span></div><div class="post-copyright__type"><span class="post-copyright-meta"><i class="fas fa-square-arrow-up-right fa-fw"></i>文章链接: </span><span class="post-copyright-info"><a href="https://rq.shenjianl.cn/posts/95.html">https://rq.shenjianl.cn/posts/95.html</a></span></div><div class="post-copyright__notice"><span class="post-copyright-meta"><i class="fas fa-circle-exclamation fa-fw"></i>版权声明: </span><span class="post-copyright-info">本博客所有文章除特别声明外，均采用 <a href="https://qr.shenjianl.cn/licenses/by-nc-sa/4.0/" target="_blank">CC BY-NC-SA 4.0</a> 许可协议。转载请注明来自 <a href="https://rq.shenjianl.cn" target="_blank">QuickReference</a>！</span></div></div><div class="tag_share"><div class="post-meta__tag-list"><a class="post-meta__tags" href="/tags/decisiontree/">decisiontree</a></div><div class="post_share"><div class="social-share" data-image="/img/avatar.jpg" data-sites="facebook,twitter,wechat,weibo,qq"></div><link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/butterfly-extsrc@1.1.3/sharejs/dist/css/share.min.css" media="print" onload="this.media='all'"><script src="https://cdn.jsdelivr.net/npm/butterfly-extsrc@1.1.3/sharejs/dist/js/social-share.min.js" defer></script></div></div><nav class="pagination-post" id="pagination"><div class="next-post pull-full"><a href="/posts/60504.html" title="逻辑回归"><div class="cover" style="background: var(--default-bg-color)"></div><div class="pagination-info"><div class="label">下一篇</div><div class="next_info">逻辑回归</div></div></a></div></nav></div><div class="aside-content" id="aside-content"><div class="card-widget card-info"><div class="is-center"><div class="avatar-img"><img src="/img/avatar.jpg" onerror="this.onerror=null;this.src='/img/friend_404.gif'" alt="avatar"/></div><div class="author-info__name">shenjianZ</div><div class="author-info__description">一份快捷简便的文档，便于查阅编程的细节</div></div><div class="card-info-data site-data is-center"><a href="/archives/"><div class="headline">文章</div><div class="length-num">17</div></a><a href="/tags/"><div class="headline">标签</div><div class="length-num">8</div></a><a href="/categories/"><div class="headline">分类</div><div class="length-num">2</div></a></div><a id="card-info-btn" target="_blank" rel="noopener" href="https://github.com/shenjianz"><i class="fab fa-github"></i><span>Follow Me</span></a><div class="card-info-social-icons is-center"><a class="social-icon" href="https://github.com/shenjianZ" target="_blank" title="Github"><i class="fab fa-github" style="color: #24292e;"></i></a><a class="social-icon" href="mailto:15202078626@163.com" target="_blank" title="Email"><i class="fas fa-envelope" style="color: #4a7dbe;"></i></a></div></div><div class="card-widget card-announcement"><div class="item-headline"><i class="fas fa-bullhorn fa-shake"></i><span>公告</span></div><div class="announcement_content">一个简单快捷的文档知识点查阅网站</div></div><div class="sticky_layout"><div class="card-widget" id="card-toc"><div class="item-headline"><i class="fas fa-stream"></i><span>目录</span><span class="toc-percentage"></span></div><div class="toc-content is-expand"><ol class="toc"><li class="toc-item toc-level-3"><a class="toc-link" href="#C4-5"><span class="toc-number">1.</span> <span class="toc-text">C4.5</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#ID3"><span class="toc-number">2.</span> <span class="toc-text">ID3</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#Cart"><span class="toc-number">3.</span> <span class="toc-text">Cart</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#cart%E5%89%AA%E6%9E%9D"><span class="toc-number">4.</span> <span class="toc-text">cart剪枝</span></a><ol class="toc-child"><li class="toc-item toc-level-4"><a class="toc-link" href="#%E9%A2%84%E5%89%AA%E6%9E%9D%EF%BC%9A"><span class="toc-number">4.1.</span> <span class="toc-text">预剪枝：</span></a></li><li class="toc-item toc-level-4"><a class="toc-link" href="#%E5%90%8E%E5%89%AA%E6%9E%9D%EF%BC%9A"><span class="toc-number">4.2.</span> <span class="toc-text">后剪枝：</span></a></li></ol></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E7%89%B9%E5%BE%81%E5%B7%A5%E7%A8%8B-%E7%89%B9%E5%BE%81%E6%8F%90%E5%8F%96"><span class="toc-number">5.</span> <span class="toc-text">特征工程(特征提取)</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#tf-idf"><span class="toc-number">6.</span> <span class="toc-text">tf-idf</span></a></li><li class="toc-item toc-level-3"><a class="toc-link" href="#%E5%9B%9E%E5%BD%92%E5%86%B3%E7%AD%96Line truncated
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