Source code for lale.lib.sklearn.polynomial_features

# Copyright 2019 IBM Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import sklearn.preprocessing.data
import lale.helpers
import lale.operators

class PolynomialFeaturesImpl():

    def __init__(self, degree=2, interaction_only=False, include_bias=None):
        self._hyperparams = {
            'degree': degree,
            'interaction_only': interaction_only,
            'include_bias': include_bias}

    def fit(self, X, y=None):
        self._sklearn_model = sklearn.preprocessing.data.PolynomialFeatures(**self._hyperparams)
        self._sklearn_model.fit(X, y)
        return self

    def transform(self, X):
        return self._sklearn_model.transform(X)
_hyperparams_schema = {
    '$schema': 'http://json-schema.org/draft-04/schema#',
    'description': 'Generate polynomial and interaction features.',
    'allOf': [{
        'type': 'object',
        'required': ['include_bias'],
        'relevantToOptimizer': ['degree', 'interaction_only','include_bias'],
        'additionalProperties': False,
        'properties': {
            'degree': {
                'type': 'integer',
                'minimumForOptimizer': 2,
                'maximumForOptimizer': 3,
                'default': 2,
                'description': 'The degree of the polynomial features. Default = 2.'},
            'interaction_only': {
                'type': 'boolean',
                'default': False,
                'description': 'If true, only interaction features are produced: features that are'},
            'include_bias': {
                'type': 'boolean',
                'default': True,
                'description': 'If True (default), then include a bias column, the feature in which'},
            # 'order':{#This is new in version 0.21. Hence commenting out for now.
            #     'enum':['F', 'C'],
            #     'default': 'C',
            #     'description':'Order of output array in the dense case. '
            #                     ''F' order is faster to compute, but may slow down subsequent estimators.' },
        }}],
}
_input_fit_schema = {
    '$schema': 'http://json-schema.org/draft-04/schema#',
    'description': 'Compute number of output features.',
    'type': 'object',
    'required': ['X'],
    'properties': {
        'X': {
            'type': 'array',
            'items': {
                'type': 'array',
                'items': {
                    'type': 'number'},
            },
            'description': 'The data.'},
    },
}
_input_transform_schema = {
    '$schema': 'http://json-schema.org/draft-04/schema#',
    'description': 'Transform data to polynomial features',
    'type': 'object',
    'required': ['X'],
    'properties': {
        'X': {
            'type': 'array',
            'items': {
                'type': 'array',
                'items': {
                    'type': 'number'},
            },
            'description': 'The data to transform, row by row.'},
    },
}
_output_transform_schema = {
    '$schema': 'http://json-schema.org/draft-04/schema#',
    'description': 'The matrix of features, where NP is the number of polynomial',
    'type': 'array',
    'items': {
        'type': 'array',
        'items': {'type': 'number'}}}

_combined_schemas = {
    '$schema': 'http://json-schema.org/draft-04/schema#',
    'description': 'Combined schema for expected data and hyperparameters.',
    'documentation_url': 'https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PolynomialFeatures.html',
    'type': 'object',
    'tags': {
        'pre': [],
        'op': ['transformer'],
        'post': []},
    'properties': {
        'hyperparams': _hyperparams_schema,
        'input_fit': _input_fit_schema,
        'input_predict': _input_transform_schema,
        'output': _output_transform_schema},
}
if (__name__ == '__main__'):
    lale.helpers.validate_is_schema(_combined_schemas)
PolynomialFeatures = lale.operators.make_operator(PolynomialFeaturesImpl, _combined_schemas)