Models

class caf.brain.ml.Models(value)

Bases: Enum

Available algorithms for the caf.brAIn prediction model.

Attributes

LOGIT_REGRESSION_L1
LOGIT_REGRESSION_L2
LOGIT_REGRESSION_ELASTICNET
MULTINOMIAL
RANDOM_FOREST_REGRESSOR
EXTRA_TREES_REGRESSOR
GRADIENT_BOOSTING_REGRESSOR
GRADIENT_BOOSTING_CLASSIFIER
ADABOOST_REGRESSOR
BAGGING_REGRESSOR
SVR
KNN
RIDGE
LASSO
ELASTICNET
LINEAR_REGRESSION
DECISION_TREE_REGRESSOR
RANDOM_FOREST_CLASSIFIER
EXTRA_TREES_CLASSIFIER
DECISION_TREE_CLASSIFIER
SVM_CLASSIFIER

Methods

get_model()

Helper method for algorithm selection and initialisation.

Attributes Documentation

LOGIT_REGRESSION_L1 = 'logit_regression_l1'

LOGIT_REGRESSION_L2 = 'logit_regression_l2'

LOGIT_REGRESSION_ELASTICNET = 'logit_regression_elasticnet'

MULTINOMIAL = 'multinomial'

RANDOM_FOREST_REGRESSOR = 'random_forest_regressor'

EXTRA_TREES_REGRESSOR = 'extra_trees_regressor'

GRADIENT_BOOSTING_REGRESSOR = 'gradient_boosting_regressor'

GRADIENT_BOOSTING_CLASSIFIER = 'gradient_boosting_classifier'

ADABOOST_REGRESSOR = 'adabost_regressor'

BAGGING_REGRESSOR = 'bagging_regressor'

SVR = 'svr'

KNN = 'knn'

RIDGE = 'ridge'

LASSO = 'lasso'

ELASTICNET = 'elasticnet'

LINEAR_REGRESSION = 'linear_regression'

DECISION_TREE_REGRESSOR = 'decision_tree_regressor'

RANDOM_FOREST_CLASSIFIER = 'random_forest_classifier'

EXTRA_TREES_CLASSIFIER = 'extra_trees_classifier'

DECISION_TREE_CLASSIFIER = 'decision_tree_classifier'

SVM_CLASSIFIER = 'svm_classifier'