13 lines
420 B
Plaintext
13 lines
420 B
Plaintext
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Again there are a couple modifiers possible
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<l2st>
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nonconst->remove constant features
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shuffle
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normalize('zscore'/'minmax')
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cut(10)->at most 10 datasets
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split->train test split, all anomalies in test set
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crossval(5)->similar to split, but do multiple times (crossvalidation)
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</l2st>
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modifiers interact with each other
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For example: normalize('minmax'), split
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->train set always below 1, but no guarantees for the test set
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