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Eddie Bergman: Update docstrings of include and exclude parameters of the estimators (#1332)
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‎development/_modules/autosklearn/estimators.html

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@@ -146,8 +146,8 @@ <h1>Source code for autosklearn.estimators</h1><div class="highlight"><pre>
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<span class="n">max_models_on_disc</span><span class="o">=</span><span class="mi">50</span><span class="p">,</span>
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<span class="n">seed</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
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<span class="n">memory_limit</span><span class="o">=</span><span class="mi">3072</span><span class="p">,</span>
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<span class="n">include</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
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<span class="n">exclude</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
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<span class="n">include</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">List</span><span class="p">[</span><span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
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<span class="n">exclude</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">List</span><span class="p">[</span><span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
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<span class="n">resampling_strategy</span><span class="o">=</span><span class="s1">&#39;holdout&#39;</span><span class="p">,</span>
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<span class="n">resampling_strategy_arguments</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
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<span class="n">tmp_folder</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
@@ -209,24 +209,63 @@ <h1>Source code for autosklearn.estimators</h1><div class="highlight"><pre>
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<span class="sd"> Memory limit in MB for the machine learning algorithm.</span>
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<span class="sd"> `auto-sklearn` will stop fitting the machine learning algorithm if</span>
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<span class="sd"> it tries to allocate more than ``memory_limit`` MB.</span>
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<span class="sd"> </span>
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<span class="sd"> **Important notes:** </span>
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<span class="sd"> </span>
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<span class="sd"> **Important notes:**</span>
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<span class="sd"> * If ``None`` is provided, no memory limit is set.</span>
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<span class="sd"> * In case of multi-processing, ``memory_limit`` will be *per job*, so the total usage is </span>
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<span class="sd"> * In case of multi-processing, ``memory_limit`` will be *per job*, so the total usage is</span>
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<span class="sd"> ``n_jobs x memory_limit``.</span>
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<span class="sd"> * The memory limit also applies to the ensemble creation process.</span>
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<span class="sd"> include : dict, optional (None)</span>
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<span class="sd"> If None, all possible algorithms are used. Otherwise specifies</span>
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<span class="sd"> set of algorithms for each added component is used. Include and </span>
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<span class="sd"> exclude are incompatible if used together on the same component</span>
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<span class="sd"> include : Optional[Dict[str, List[str]]] = None</span>
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<span class="sd"> If None, all possible algorithms are used.</span>
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<span class="sd"> Otherwise, specifies a step and the components that are included in search.</span>
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<span class="sd"> See ``/pipeline/components/&lt;step&gt;/*`` for available components.</span>
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<span class="sd"> Incompatible with parameter ``exclude``.</span>
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<span class="sd"> **Possible Steps**:</span>
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<span class="sd"> * ``&quot;data_preprocessor&quot;``</span>
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<span class="sd"> * ``&quot;balancing&quot;``</span>
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<span class="sd"> * ``&quot;feature_preprocessor&quot;``</span>
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<span class="sd"> * ``&quot;classifier&quot;`` - Only for when when using ``AutoSklearnClasssifier``</span>
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<span class="sd"> * ``&quot;regressor&quot;`` - Only for when when using ``AutoSklearnRegressor``</span>
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<span class="sd"> **Example**:</span>
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<span class="sd"> .. code-block:: python</span>
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<span class="sd"> include = {</span>
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<span class="sd"> &#39;classifier&#39;: [&quot;random_forest&quot;],</span>
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<span class="sd"> &#39;feature_preprocessor&#39;: [&quot;no_preprocessing&quot;]</span>
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<span class="sd"> }</span>
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<span class="sd"> exclude : Optional[Dict[str, List[str]]] = None</span>
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<span class="sd"> If None, all possible algorithms are used.</span>
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<span class="sd"> Otherwise, specifies a step and the components that are excluded from search.</span>
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<span class="sd"> See ``/pipeline/components/&lt;step&gt;/*`` for available components.</span>
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<span class="sd"> Incompatible with parameter ``include``.</span>
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<span class="sd"> **Possible Steps**:</span>
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<span class="sd"> * ``&quot;data_preprocessor&quot;``</span>
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<span class="sd"> * ``&quot;balancing&quot;``</span>
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<span class="sd"> * ``&quot;feature_preprocessor&quot;``</span>
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<span class="sd"> * ``&quot;classifier&quot;`` - Only for when when using ``AutoSklearnClasssifier``</span>
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<span class="sd"> * ``&quot;regressor&quot;`` - Only for when when using ``AutoSklearnRegressor``</span>
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<span class="sd"> **Example**:</span>
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<span class="sd"> .. code-block:: python</span>
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<span class="sd"> exclude : dict, optional (None)</span>
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<span class="sd"> If None, all possible algorithms are used. Otherwise specifies</span>
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<span class="sd"> set of algorithms for each added component is not used.</span>
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<span class="sd"> Incompatible with include. Include and exclude are incompatible</span>
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<span class="sd"> if used together on the same component</span>
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<span class="sd"> exclude = {</span>
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<span class="sd"> &#39;classifier&#39;: [&quot;random_forest&quot;],</span>
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<span class="sd"> &#39;feature_preprocessor&#39;: [&quot;no_preprocessing&quot;]</span>
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<span class="sd"> }</span>
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<span class="sd"> resampling_strategy : string or object, optional (&#39;holdout&#39;)</span>
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<span class="sd"> how to to handle overfitting, might need &#39;resampling_strategy_arguments&#39;</span>

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