Pushing the docs to dev/ for branch: master, commit 747b43fb03126de5cb26e2090d6ecd93943a2dd7

Author: skoptci

dev/_downloads/0291a47bd3f63e064c434aea964d8e66/bayesian-optimization.ipynb

@@ -208,7 +208,7 @@
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dev/_downloads/0f0d53351b0405c47cf8d0ef671596f9/interruptible-optimization.ipynb

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       "name": "python",
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       "pygments_lexer": "ipython3",
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dev/_downloads/227fbc11d592826e298cb4f679fc86b8/optimizer-with-different-base-estimator.ipynb

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       "pygments_lexer": "ipython3",
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dev/_downloads/2836dfc666978d3b8e63b1399cca6c8a/sampling_comparison.ipynb

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       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
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dev/_downloads/2aff3ba2ab1c0ff8a9636a15622dc4c4/parallel-optimization.ipynb

@@ -71,7 +71,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
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dev/_downloads/327b9e59a928801e7cc2b01a757db508/partial-dependence-plot.ipynb

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       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
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dev/_downloads/3409d9766d352cc9f9b169d4a799a87a/auto_examples_python.zip

@@ -15,7 +15,7 @@
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-        "\n# Tuning a scikit-learn estimator with `skopt`\n\nGilles Louppe, July 2016\nKatie Malone, August 2016\nReformatted by Holger Nahrstaedt 2020\n\n.. currentmodule:: skopt\n\nIf you are looking for a :obj:`sklearn.model_selection.GridSearchCV` replacement checkout\n`sphx_glr_auto_examples_sklearn-gridsearchcv-replacement.py` instead.\n\n## Problem statement\n\nTuning the hyper-parameters of a machine learning model is often carried out\nusing an exhaustive exploration of (a subset of) the space all hyper-parameter\nconfigurations (e.g., using :obj:`sklearn.model_selection.GridSearchCV`), which\noften results in a very time consuming operation.\n\nIn this notebook, we illustrate how to couple :class:`gp_minimize` with sklearn's\nestimators to tune hyper-parameters using sequential model-based optimisation,\nhopefully resulting in equivalent or better solutions, but within less\nevaluations.\n\nNote: scikit-optimize provides a dedicated interface for estimator tuning via\n:class:`BayesSearchCV` class which has a similar interface to those of\n:obj:`sklearn.model_selection.GridSearchCV`. This class uses functions of skopt to perform hyperparameter\nsearch efficiently. For example usage of this class, see\n`sphx_glr_auto_examples_sklearn-gridsearchcv-replacement.py`\nexample notebook.\n"
+        "\n# Tuning a scikit-learn estimator with `skopt`\n\nGilles Louppe, July 2016\nKatie Malone, August 2016\nReformatted by Holger Nahrstaedt 2020\n\n.. currentmodule:: skopt\n\nIf you are looking for a :obj:`sklearn.model_selection.GridSearchCV` replacement checkout\n`sphx_glr_auto_examples_sklearn-gridsearchcv-replacement.py` instead.\n\n## Problem statement\n\nTuning the hyper-parameters of a machine learning model is often carried out\nusing an exhaustive exploration of (a subset of) the space all hyper-parameter\nconfigurations (e.g., using :obj:`sklearn.model_selection.GridSearchCV`), which\noften results in a very time consuming operation.\n\nIn this notebook, we illustrate how to couple :class:`gp_minimize` with sklearn's\nestimators to tune hyper-parameters using sequential model-based optimisation,\nhopefully resulting in equivalent or better solutions, but within fewer\nevaluations.\n\nNote: scikit-optimize provides a dedicated interface for estimator tuning via\n:class:`BayesSearchCV` class which has a similar interface to those of\n:obj:`sklearn.model_selection.GridSearchCV`. This class uses functions of skopt to perform hyperparameter\nsearch efficiently. For example usage of this class, see\n`sphx_glr_auto_examples_sklearn-gridsearchcv-replacement.py`\nexample notebook.\n"
       ]
     },
     {
@@ -129,7 +129,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.9.4"
+      "version": "3.9.5"
     }
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   "nbformat": 4,

dev/_downloads/659de5944f8dc1f0424c48f86a240d84/hyperparameter-optimization.ipynb

@@ -154,7 +154,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.9.4"
+      "version": "3.9.5"
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dev/_downloads/6bf99924122eedf93b886bae30f1182b/sklearn-gridsearchcv-replacement.ipynb

@@ -183,7 +183,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.9.4"
+      "version": "3.9.5"
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