|  | import{_ as e,o as n,c as i,a as s,f as a}from"./app-AOepGS68.js";const t={},r=a(`<h2 id="机器学习" tabindex="-1"><a class="header-anchor" href="#机器学习" aria-hidden="true">#</a> 机器学习</h2><h3 id="ar" tabindex="-1"><a class="header-anchor" href="#ar" aria-hidden="true">#</a> AR</h3><h4 id="函数简介" tabindex="-1"><a class="header-anchor" href="#函数简介" aria-hidden="true">#</a> 函数简介</h4><p>本函数用于学习数据的自回归模型系数。</p><p><strong>函数名:</strong> AR</p><p><strong>输入序列:</strong> 仅支持单个输入序列,类型为 INT32 / INT64 / FLOAT / DOUBLE。</p><p><strong>参数:</strong></p><ul><li><code>p</code>:自回归模型的阶数。默认为1。</li></ul><p><strong>输出序列:</strong> 输出单个序列,类型为 DOUBLE。第一行对应模型的一阶系数,以此类推。</p><p><strong>提示:</strong></p><ul><li><p><code>p</code>应为正整数。</p></li><li><p>序列中的大部分点为等间隔采样点。</p></li><li><p>序列中的缺失点通过线性插值进行填补后用于学习过程。</p></li></ul><h4 id="使用示例" tabindex="-1"><a class="header-anchor" href="#使用示例" aria-hidden="true">#</a> 使用示例</h4><h5 id="指定阶数" tabindex="-1"><a class="header-anchor" href="#指定阶数" aria-hidden="true">#</a> 指定阶数</h5><p>输入序列:</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>+-----------------------------+---------------+ | 
|  | |                         Time|root.test.d0.s0| | 
|  | +-----------------------------+---------------+ | 
|  | |2020-01-01T00:00:01.000+08:00|           -4.0| | 
|  | |2020-01-01T00:00:02.000+08:00|           -3.0| | 
|  | |2020-01-01T00:00:03.000+08:00|           -2.0| | 
|  | |2020-01-01T00:00:04.000+08:00|           -1.0| | 
|  | |2020-01-01T00:00:05.000+08:00|            0.0| | 
|  | |2020-01-01T00:00:06.000+08:00|            1.0| | 
|  | |2020-01-01T00:00:07.000+08:00|            2.0| | 
|  | |2020-01-01T00:00:08.000+08:00|            3.0| | 
|  | |2020-01-01T00:00:09.000+08:00|            4.0| | 
|  | +-----------------------------+---------------+ | 
|  | </code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div><p>用于查询的 SQL 语句:</p><div class="language-sql line-numbers-mode" data-ext="sql"><pre class="language-sql"><code><span class="token keyword">select</span> ar<span class="token punctuation">(</span>s0<span class="token punctuation">,</span><span class="token string">"p"</span><span class="token operator">=</span><span class="token string">"2"</span><span class="token punctuation">)</span> <span class="token keyword">from</span> root<span class="token punctuation">.</span>test<span class="token punctuation">.</span>d0 | 
|  | </code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div></div></div><p>输出序列:</p><div class="language-text line-numbers-mode" data-ext="text"><pre class="language-text"><code>+-----------------------------+---------------------------+ | 
|  | |                         Time|ar(root.test.d0.s0,"p"="2")| | 
|  | +-----------------------------+---------------------------+ | 
|  | |1970-01-01T08:00:00.001+08:00|                     0.9429| | 
|  | |1970-01-01T08:00:00.002+08:00|                    -0.2571| | 
|  | +-----------------------------+---------------------------+ | 
|  | </code></pre><div class="line-numbers" aria-hidden="true"><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div><div class="line-number"></div></div></div>`,19);function d(l,o){return n(),i("div",null,[s(` | 
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|  | `),r])}const u=e(t,[["render",d],["__file","Machine-Learning.html.vue"]]);export{u as default}; |