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Ravin Kohli: [ADD] variance thresholding (#373)
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8 changes: 4 additions & 4 deletions development/_modules/autoPyTorch/api/tabular_classification.html
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<meta name='viewport' content='width=device-width, initial-scale=1.0, maximum-scale=1'>
<meta name="apple-mobile-web-app-capable" content="yes">
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8 changes: 4 additions & 4 deletions development/_modules/autoPyTorch/api/tabular_regression.html
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<meta http-equiv='X-UA-Compatible' content='IE=edge,chrome=1'>
<meta name='viewport' content='width=device-width, initial-scale=1.0, maximum-scale=1'>
<meta name="apple-mobile-web-app-capable" content="yes">
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<meta http-equiv='X-UA-Compatible' content='IE=edge,chrome=1'>
<meta name='viewport' content='width=device-width, initial-scale=1.0, maximum-scale=1'>
<meta name="apple-mobile-web-app-capable" content="yes">
<script type="text/javascript" src="../../../../_static/js/jquery-1.12.4.min.js "></script>
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8 changes: 4 additions & 4 deletions development/_modules/autoPyTorch/pipeline/components/base_component.html
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<meta http-equiv='X-UA-Compatible' content='IE=edge,chrome=1'>
<meta name='viewport' content='width=device-width, initial-scale=1.0, maximum-scale=1'>
<meta name="apple-mobile-web-app-capable" content="yes">
<script type="text/javascript" src="../../../../_static/js/jquery-1.12.4.min.js "></script>
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11 changes: 7 additions & 4 deletions development/_modules/autoPyTorch/pipeline/tabular_classification.html
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<meta http-equiv='X-UA-Compatible' content='IE=edge,chrome=1'>
<meta name='viewport' content='width=device-width, initial-scale=1.0, maximum-scale=1'>
<meta name="apple-mobile-web-app-capable" content="yes">
<script type="text/javascript" src="../../../_static/js/jquery-1.12.4.min.js "></script>
<script type="text/javascript" src="../../../_static/js/jquery-fix.js "></script>
<script type="text/javascript" src="../../../_static/bootstrap-3.4.1/js/bootstrap.min.js "></script>
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<script type="text/javascript" src="../../../_static/js/jquery-1.12.4.min.js"></script>
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Expand Down Expand Up @@ -140,6 +140,8 @@ <h1>Source code for autoPyTorch.pipeline.tabular_classification</h1><div class="
<span class="p">)</span>
<span class="kn">from</span> <span class="nn">autoPyTorch.pipeline.components.preprocessing.tabular_preprocessing.imputation.SimpleImputer</span> <span class="kn">import</span> <span class="n">SimpleImputer</span>
<span class="kn">from</span> <span class="nn">autoPyTorch.pipeline.components.preprocessing.tabular_preprocessing.scaling</span> <span class="kn">import</span> <span class="n">ScalerChoice</span>
<span class="kn">from</span> <span class="nn">autoPyTorch.pipeline.components.preprocessing.tabular_preprocessing.variance_thresholding.</span> \
<span class="n">VarianceThreshold</span> <span class="kn">import</span> <span class="nn">VarianceThreshold</span>
<span class="kn">from</span> <span class="nn">autoPyTorch.pipeline.components.setup.early_preprocessor.EarlyPreprocessing</span> <span class="kn">import</span> <span class="n">EarlyPreprocessing</span>
<span class="kn">from</span> <span class="nn">autoPyTorch.pipeline.components.setup.lr_scheduler</span> <span class="kn">import</span> <span class="n">SchedulerChoice</span>
<span class="kn">from</span> <span class="nn">autoPyTorch.pipeline.components.setup.network.base_network</span> <span class="kn">import</span> <span class="n">NetworkComponent</span>
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<span class="n">steps</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span>
<span class="p">(</span><span class="s2">&quot;imputer&quot;</span><span class="p">,</span> <span class="n">SimpleImputer</span><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">random_state</span><span class="p">)),</span>
<span class="p">(</span><span class="s2">&quot;variance_threshold&quot;</span><span class="p">,</span> <span class="n">VarianceThreshold</span><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">random_state</span><span class="p">)),</span>
<span class="p">(</span><span class="s2">&quot;encoder&quot;</span><span class="p">,</span> <span class="n">EncoderChoice</span><span class="p">(</span><span class="n">default_dataset_properties</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">random_state</span><span class="p">)),</span>
<span class="p">(</span><span class="s2">&quot;scaler&quot;</span><span class="p">,</span> <span class="n">ScalerChoice</span><span class="p">(</span><span class="n">default_dataset_properties</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">random_state</span><span class="p">)),</span>
<span class="p">(</span><span class="s2">&quot;feature_preprocessor&quot;</span><span class="p">,</span> <span class="n">FeatureProprocessorChoice</span><span class="p">(</span><span class="n">default_dataset_properties</span><span class="p">,</span>
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11 changes: 7 additions & 4 deletions development/_modules/autoPyTorch/pipeline/tabular_regression.html
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<meta http-equiv='X-UA-Compatible' content='IE=edge,chrome=1'>
<meta name='viewport' content='width=device-width, initial-scale=1.0, maximum-scale=1'>
<meta name="apple-mobile-web-app-capable" content="yes">
<script type="text/javascript" src="../../../_static/js/jquery-1.12.4.min.js "></script>
<script type="text/javascript" src="../../../_static/js/jquery-fix.js "></script>
<script type="text/javascript" src="../../../_static/bootstrap-3.4.1/js/bootstrap.min.js "></script>
<script type="text/javascript" src="../../../_static/bootstrap-sphinx.js "></script>
<script type="text/javascript" src="../../../_static/js/jquery-1.12.4.min.js"></script>
<script type="text/javascript" src="../../../_static/js/jquery-fix.js"></script>
<script type="text/javascript" src="../../../_static/bootstrap-3.4.1/js/bootstrap.min.js"></script>
<script type="text/javascript" src="../../../_static/bootstrap-sphinx.js"></script>

</head><body>

Expand Down Expand Up @@ -140,6 +140,8 @@ <h1>Source code for autoPyTorch.pipeline.tabular_regression</h1><div class="high
<span class="p">)</span>
<span class="kn">from</span> <span class="nn">autoPyTorch.pipeline.components.preprocessing.tabular_preprocessing.imputation.SimpleImputer</span> <span class="kn">import</span> <span class="n">SimpleImputer</span>
<span class="kn">from</span> <span class="nn">autoPyTorch.pipeline.components.preprocessing.tabular_preprocessing.scaling</span> <span class="kn">import</span> <span class="n">ScalerChoice</span>
<span class="kn">from</span> <span class="nn">autoPyTorch.pipeline.components.preprocessing.tabular_preprocessing.variance_thresholding.</span> \
<span class="n">VarianceThreshold</span> <span class="kn">import</span> <span class="nn">VarianceThreshold</span>
<span class="kn">from</span> <span class="nn">autoPyTorch.pipeline.components.setup.early_preprocessor.EarlyPreprocessing</span> <span class="kn">import</span> <span class="n">EarlyPreprocessing</span>
<span class="kn">from</span> <span class="nn">autoPyTorch.pipeline.components.setup.lr_scheduler</span> <span class="kn">import</span> <span class="n">SchedulerChoice</span>
<span class="kn">from</span> <span class="nn">autoPyTorch.pipeline.components.setup.network.base_network</span> <span class="kn">import</span> <span class="n">NetworkComponent</span>
Expand Down Expand Up @@ -370,6 +372,7 @@ <h1>Source code for autoPyTorch.pipeline.tabular_regression</h1><div class="high

<span class="n">steps</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span>
<span class="p">(</span><span class="s2">&quot;imputer&quot;</span><span class="p">,</span> <span class="n">SimpleImputer</span><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">random_state</span><span class="p">)),</span>
<span class="p">(</span><span class="s2">&quot;variance_threshold&quot;</span><span class="p">,</span> <span class="n">VarianceThreshold</span><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">random_state</span><span class="p">)),</span>
<span class="p">(</span><span class="s2">&quot;encoder&quot;</span><span class="p">,</span> <span class="n">EncoderChoice</span><span class="p">(</span><span class="n">default_dataset_properties</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">random_state</span><span class="p">)),</span>
<span class="p">(</span><span class="s2">&quot;scaler&quot;</span><span class="p">,</span> <span class="n">ScalerChoice</span><span class="p">(</span><span class="n">default_dataset_properties</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">random_state</span><span class="p">)),</span>
<span class="p">(</span><span class="s2">&quot;feature_preprocessor&quot;</span><span class="p">,</span> <span class="n">FeatureProprocessorChoice</span><span class="p">(</span><span class="n">default_dataset_properties</span><span class="p">,</span>
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8 changes: 4 additions & 4 deletions development/_modules/autoPyTorch/pipeline/traditional_tabular_classification.html
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<meta http-equiv='X-UA-Compatible' content='IE=edge,chrome=1'>
<meta name='viewport' content='width=device-width, initial-scale=1.0, maximum-scale=1'>
<meta name="apple-mobile-web-app-capable" content="yes">
<script type="text/javascript" src="../../../_static/js/jquery-1.12.4.min.js "></script>
<script type="text/javascript" src="../../../_static/js/jquery-fix.js "></script>
<script type="text/javascript" src="../../../_static/bootstrap-3.4.1/js/bootstrap.min.js "></script>
<script type="text/javascript" src="../../../_static/bootstrap-sphinx.js "></script>
<script type="text/javascript" src="../../../_static/js/jquery-1.12.4.min.js"></script>
<script type="text/javascript" src="../../../_static/js/jquery-fix.js"></script>
<script type="text/javascript" src="../../../_static/bootstrap-3.4.1/js/bootstrap.min.js"></script>
<script type="text/javascript" src="../../../_static/bootstrap-sphinx.js"></script>

</head><body>

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<meta http-equiv='X-UA-Compatible' content='IE=edge,chrome=1'>
<meta name='viewport' content='width=device-width, initial-scale=1.0, maximum-scale=1'>
<meta name="apple-mobile-web-app-capable" content="yes">
<script type="text/javascript" src="../../../_static/js/jquery-1.12.4.min.js "></script>
<script type="text/javascript" src="../../../_static/js/jquery-fix.js "></script>
<script type="text/javascript" src="../../../_static/bootstrap-3.4.1/js/bootstrap.min.js "></script>
<script type="text/javascript" src="../../../_static/bootstrap-sphinx.js "></script>
<script type="text/javascript" src="../../../_static/js/jquery-1.12.4.min.js"></script>
<script type="text/javascript" src="../../../_static/js/jquery-fix.js"></script>
<script type="text/javascript" src="../../../_static/bootstrap-3.4.1/js/bootstrap.min.js"></script>
<script type="text/javascript" src="../../../_static/bootstrap-sphinx.js"></script>

</head><body>

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<meta http-equiv='X-UA-Compatible' content='IE=edge,chrome=1'>
<meta name='viewport' content='width=device-width, initial-scale=1.0, maximum-scale=1'>
<meta name="apple-mobile-web-app-capable" content="yes">
<script type="text/javascript" src="../_static/js/jquery-1.12.4.min.js "></script>
<script type="text/javascript" src="../_static/js/jquery-fix.js "></script>
<script type="text/javascript" src="../_static/bootstrap-3.4.1/js/bootstrap.min.js "></script>
<script type="text/javascript" src="../_static/bootstrap-sphinx.js "></script>
<script type="text/javascript" src="../_static/js/jquery-1.12.4.min.js"></script>
<script type="text/javascript" src="../_static/js/jquery-fix.js"></script>
<script type="text/javascript" src="../_static/bootstrap-3.4.1/js/bootstrap.min.js"></script>
<script type="text/javascript" src="../_static/bootstrap-sphinx.js"></script>

</head><body>

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31 changes: 14 additions & 17 deletions development/_sources/examples/20_basics/example_image_classification.rst.txt
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Expand Up @@ -84,28 +84,25 @@ Image Classification

Pipeline Random Config:
________________________________________
Configuration:
image_augmenter:GaussianBlur:sigma_min, Value: 2.4981384751028837
image_augmenter:GaussianBlur:sigma_offset, Value: 1.3265778731850062
image_augmenter:GaussianBlur:use_augmenter, Value: True
image_augmenter:GaussianNoise:use_augmenter, Value: False
image_augmenter:RandomAffine:rotate, Value: 332
image_augmenter:RandomAffine:scale_offset, Value: 0.20046574757452593
image_augmenter:RandomAffine:shear, Value: 31
image_augmenter:RandomAffine:translate_percent_offset, Value: 0.14608328354295247
image_augmenter:RandomAffine:use_augmenter, Value: True
image_augmenter:RandomCutout:p, Value: 0.2648052996462756
image_augmenter:RandomCutout:use_augmenter, Value: True
image_augmenter:Resize:use_augmenter, Value: False
image_augmenter:ZeroPadAndCrop:percent, Value: 0.17842798149849115
normalizer:__choice__, Value: 'NoNormalizer'
Configuration(values={
'image_augmenter:GaussianBlur:sigma_min': 2.5825628129058305,
'image_augmenter:GaussianBlur:sigma_offset': 0.4548687619380444,
'image_augmenter:GaussianBlur:use_augmenter': True,
'image_augmenter:GaussianNoise:sigma_offset': 2.065404323877688,
'image_augmenter:GaussianNoise:use_augmenter': True,
'image_augmenter:RandomAffine:use_augmenter': False,
'image_augmenter:RandomCutout:use_augmenter': False,
'image_augmenter:Resize:use_augmenter': False,
'image_augmenter:ZeroPadAndCrop:percent': 0.0806044230263594,
'normalizer:__choice__': 'ImageNormalizer',
})

Fitting the pipeline...
________________________________________
ImageClassificationPipeline
________________________________________
0-) normalizer:
NoNormalizer
ImageNormalizer

1-) preprocessing:
EarlyPreprocessing
Expand Down Expand Up @@ -177,7 +174,7 @@ Image Classification
.. rst-class:: sphx-glr-timing

**Total running time of the script:** ( 0 minutes 8.128 seconds)
**Total running time of the script:** ( 0 minutes 6.799 seconds)


.. _sphx_glr_download_examples_20_basics_example_image_classification.py:
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