<p dir="auto">Hi guys,<br>
I have a hard time struggling with parameter tuning for most of the models in the scikit. I'm a machine learning student and I'm using scikit at various projects. I know in theory how each ML technique works and what is its goal but still I have a hard time figuring out what most of the parameters a model takes in the constructor means. I think a more detailed documentation should be available. The names of the parameters are rarely self explaining and most of the time the details covered on their explanation is tautological. Parameter and hyper-parameter tuning for ML models is tricky. But I find it more obscure when I cannot apply my intuition because I have no idea what a parameter is actually doing/meaning.<br>
I think most of new comers and users will find your platform more easy to understand and efficiently use if there is a detailed explanation for the parameters and the models / algorithm / objective functions that are used under the hood of scikit.<br>
Thanks</p>
<p dir="auto">Here is an overview of the work done so far relating to plotting:</p>
<ul dir="auto">
<li><a class="issue-link js-issue-link" data-error-text="Failed to load title" data-id="209259470" data-permission-text="Title is private" data-url="https://github.com/scikit-learn/scikit-learn/issues/8425" data-hovercard-type="issue" data-hovercard-url="/scikit-learn/scikit-learn/issues/8425/hovercard" href="https://github.com/scikit-learn/scikit-learn/issues/8425">#8425</a> - Decision Regions of Classifiers</li>
<li><a class="issue-link js-issue-link" data-error-text="Failed to load title" data-id="237109727" data-permission-text="Title is private" data-url="https://github.com/scikit-learn/scikit-learn/issues/9173" data-hovercard-type="pull_request" data-hovercard-url="/scikit-learn/scikit-learn/pull/9173/hovercard" href="https://github.com/scikit-learn/scikit-learn/pull/9173">#9173</a> - Confusion matrix and grid search</li>
<li><a class="issue-link js-issue-link" data-error-text="Failed to load title" data-id="209259470" data-permission-text="Title is private" data-url="https://github.com/scikit-learn/scikit-learn/issues/8425" data-hovercard-type="issue" data-hovercard-url="/scikit-learn/scikit-learn/issues/8425/hovercard" href="https://github.com/scikit-learn/scikit-learn/issues/8425">#8425</a> - Calibration curve</li>
<li><a class="issue-link js-issue-link" data-error-text="Failed to load title" data-id="381327375" data-permission-text="Title is private" data-url="https://github.com/scikit-learn/scikit-learn/issues/12599" data-hovercard-type="pull_request" data-hovercard-url="/scikit-learn/scikit-learn/pull/12599/hovercard" href="https://github.com/scikit-learn/scikit-learn/pull/12599">#12599</a> - Partial Dependence</li>
</ul>
<p dir="auto">To help control the scope of <code class="notranslate">sklearn.plot</code>, I propose we only do plotting on the axes level and <strong>not</strong> the figure level. The user would pass in the axes as a keyword. As a convenience, the default of <code class="notranslate">axes</code> will be <code class="notranslate">None</code>. Only in this case, will the plotting function generate a axes/figure to plot on.</p>