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sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(ct=sklearn.compose._column_transformer.ColumnTransformer(remainder=sklearn.preprocessing._data.StandardScaler,log10=Log_Trans.Log_Trans),poly=sklearn.preprocessing._polynomial.PolynomialFeatures,feature_select=sklearn.feature_selection._univariate_selection.SelectPercentile,model=sklearn.linear_model._glm.glm.PoissonRegressor)) (1)
Exhaustive search over specified parameter values for an estimator. Important members are fit, predict. GridSearchCV implements a "fit" and a "score" method. It also implements "score_samples",…
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sklearn.pipeline.Pipeline(ct=sklearn.compose._column_transformer.ColumnTransformer(remainder=sklearn.preprocessing._data.StandardScaler,log10=Log_Trans.Log_Trans),poly=sklearn.preprocessing._polynomial.PolynomialFeatures,feature_select=sklearn.feature_selection._univariate_selection.SelectPercentile,model=sklearn.linear_model._glm.glm.PoissonRegressor) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement…
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sklearn.compose._column_transformer.ColumnTransformer(remainder=sklearn.preprocessing._data.StandardScaler,log10=Log_Trans.Log_Trans) (1)
Applies transformers to columns of an array or pandas DataFrame. This estimator allows different columns or column subsets of the input to be transformed separately and the features generated by each…
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sklearn.preprocessing._data.StandardScaler (11)
Standardize features by removing the mean and scaling to unit variance. The standard score of a sample `x` is calculated as: z = (x - u) / s where `u` is the mean of the training samples or zero if…
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Log_Trans.Log_Trans (1)
Use log10 transformation.
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sklearn.preprocessing._polynomial.PolynomialFeatures (1)
Generate polynomial and interaction features. Generate a new feature matrix consisting of all polynomial combinations of the features with degree less than or equal to the specified degree. For…
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sklearn.feature_selection._univariate_selection.SelectPercentile (2)
Select features according to a percentile of the highest scores.
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sklearn.linear_model._glm.glm.PoissonRegressor (1)
Generalized Linear Model with a Poisson distribution. This regressor uses the 'log' link function.
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