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3ba35918a3
* Add sum of squares deviations * Calculate population variance * Add VarianceThreshold - feature selection transformer * Add docs about VarianceThreshold * Add missing code for pipeline usage
61 lines
1.6 KiB
Markdown
61 lines
1.6 KiB
Markdown
# Variance Threshold
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`VarianceThreshold` is a simple baseline approach to feature selection.
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It removes all features whose variance doesn’t meet some threshold.
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By default, it removes all zero-variance features, i.e. features that have the same value in all samples.
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## Constructor Parameters
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* $threshold (float) - features with a variance lower than this threshold will be removed (default 0.0)
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```php
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use Phpml\FeatureSelection\VarianceThreshold;
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$transformer = new VarianceThreshold(0.15);
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```
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## Example of use
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As an example, suppose that we have a dataset with boolean features and
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we want to remove all features that are either one or zero (on or off)
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in more than 80% of the samples.
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Boolean features are Bernoulli random variables, and the variance of such
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variables is given by
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```
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Var[X] = p(1 - p)
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```
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so we can select using the threshold .8 * (1 - .8):
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```php
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use Phpml\FeatureSelection\VarianceThreshold;
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$samples = [[0, 0, 1], [0, 1, 0], [1, 0, 0], [0, 1, 1], [0, 1, 0], [0, 1, 1]];
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$transformer = new VarianceThreshold(0.8 * (1 - 0.8));
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$transformer->fit($samples);
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$transformer->transform($samples);
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/*
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$samples = [[0, 1], [1, 0], [0, 0], [1, 1], [1, 0], [1, 1]];
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*/
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```
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## Pipeline
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`VarianceThreshold` implements `Transformer` interface so it can be used as part of pipeline:
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```php
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use Phpml\FeatureSelection\VarianceThreshold;
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use Phpml\Classification\SVC;
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use Phpml\FeatureExtraction\TfIdfTransformer;
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use Phpml\Pipeline;
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$transformers = [
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new TfIdfTransformer(),
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new VarianceThreshold(0.1)
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];
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$estimator = new SVC();
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$pipeline = new Pipeline($transformers, $estimator);
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```
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