Feature Neutralizer

API reference for sovai.extensions.feature_neutralizer

Module: sovai.extensions.feature_neutralizer

Functions

gram_schmidt_orthogonalization()

def gram_schmidt_orthogonalization(df)

Applies Gram-Schmidt process to orthogonalize the features of the DataFrame. Returns a new DataFrame with orthogonalized features in the original scale.

Parameters

Parameter	Type	Description
df	—	—

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pca_neutralization()

def pca_neutralization(df)

Neutralizes features using PCA by removing all but the last principal component.

Parameters

Parameter	Type	Description
df	—	—

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qr_neutralization()

def qr_neutralization(df)

Neutralizes features using QR decomposition.

Parameters

Parameter	Type	Description
df	—	—

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svd_neutralization()

def svd_neutralization(df)

Neutralizes features using SVD by setting all but the smallest singular value to zero.

Parameters

Parameter	Type	Description
df	—	—

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iterative_regression_neutralization()

def iterative_regression_neutralization(df, max_iter = 100, tol = 1e-06)

Neutralizes features using iterative regression.

Parameters

Parameter	Type	Description
df	—	—
max_iter	—	Default: 100
tol	—	Default: 1e-06

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orthogonalize_features_function()

def orthogonalize_features_function(df, method = 'gram_schmidt')

Orthogonalizes the features of the DataFrame using the specified method.

Parameters

Parameter	Type	Description
method	str	Method to use for orthogonalization. Options: 'gram_schmidt', 'qr'

Returns

CustomDataFrame: DataFrame with orthogonalized features

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neutralize_features_function()

def neutralize_features_function(df, method = 'pca')

Neutralizes the features of the DataFrame using the specified method.

Parameters

Parameter	Type	Description
method	str	Method to use for neutralization. Options: 'pca', 'svd', 'iterative_regression'

Returns

CustomDataFrame: DataFrame with neutralized features

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