oddt.scoring.models package

Submodules

oddt.scoring.models.classifiers module

oddt.scoring.models.classifiers.randomforest

alias of RandomForestClassifier

oddt.scoring.models.classifiers.svm

alias of SVC

oddt.scoring.models.neuralnetwork module

class oddt.scoring.models.neuralnetwork.neuralnetwork(shape=None, full_conn=True, biases=True, random_weights=True, normalize=True, reduce_empty_dims=True)[source]

Bases: object

shape: shape of a NN given as a tuple

Methods

fit(input_descriptors, target_values[, ...])
get_params([deep])
predict(input_descriptors)
score(X, y)
set_params(args)
fit(input_descriptors, target_values, train_alg='tnc', **kwargs)[source]
get_params(deep=True)[source]
predict(input_descriptors)[source]
score(X, y)[source]
set_params(args)[source]

oddt.scoring.models.regressors module

Collection of regressors models

oddt.scoring.models.regressors.randomforest

alias of RandomForestRegressor

oddt.scoring.models.regressors.svm

alias of SVR

oddt.scoring.models.regressors.pls

alias of PLSRegression

class oddt.scoring.models.regressors.neuralnetwork(shape=None, full_conn=True, biases=True, random_weights=True, normalize=True, reduce_empty_dims=True)[source]

Bases: object

shape: shape of a NN given as a tuple

Methods

fit(input_descriptors, target_values[, ...])
get_params([deep])
predict(input_descriptors)
score(X, y)
set_params(args)
fit(input_descriptors, target_values, train_alg='tnc', **kwargs)[source]
get_params(deep=True)[source]
predict(input_descriptors)[source]
score(X, y)[source]
set_params(args)[source]
oddt.scoring.models.regressors.mlr

alias of LinearRegression

Module contents