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<section id="bayessearchcv-a-gridsearchcv-compatible-estimator">
<span id="bayessearchcv"></span><h1><span class="section-number">2. </span>BayesSearchCV, a GridSearchCV compatible estimator<a class="headerlink" href="#bayessearchcv-a-gridsearchcv-compatible-estimator" title="Permalink to this headline">¶</a></h1>
<p>Use <code class="docutils literal notranslate"><span class="pre">BayesSearchCV</span></code> as a replacement for scikit-learn’s GridSearchCV.</p>
<p>BayesSearchCV implements a “fit” and a “score” method.
It also implements “predict”, “predict_proba”, “decision_function”,
“transform” and “inverse_transform” if they are implemented in the
estimator used.</p>
<p>The parameters of the estimator used to apply these methods are optimized
by cross-validated search over parameter settings.</p>
<p>In contrast to GridSearchCV, not all parameter values are tried out, but
rather a fixed number of parameter settings is sampled from the specified
distributions. The number of parameter settings that are tried is
given by n_iter.</p>
<p>Parameters are presented as a list of <code class="xref py py-class docutils literal notranslate"><span class="pre">skopt.space.Dimension</span></code> objects.</p>
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