oddt.scoring.models package¶
Submodules¶
oddt.scoring.models.classifiers module¶
-
oddt.scoring.models.classifiers.
randomforest
¶ alias of
RandomForestClassifier
-
class
oddt.scoring.models.classifiers.
svm
(*args, **kwargs)[source]¶ Bases:
sklearn.base.ClassifierMixin
Assemble a proper SVM classifier
Methods
fit
(descs, target_values, **kwargs)get_params
([deep])predict
(descs)score
(descs, target_values)set_params
(**kwargs)
-
class
oddt.scoring.models.classifiers.
neuralnetwork
(*args, **kwargs)[source]¶ Bases:
sklearn.base.ClassifierMixin
Assemble Neural network using sklearn tools plus ffnet wrapper
Methods
fit
(descs, target_values, **kwargs)get_params
([deep])predict
(descs)score
(descs, target_values)set_params
(**kwargs)
oddt.scoring.models.neuralnetwork module¶
oddt.scoring.models.regressors module¶
Collection of regressors models
-
oddt.scoring.models.regressors.
randomforest
¶ alias of
RandomForestRegressor
-
class
oddt.scoring.models.regressors.
svm
(*args, **kwargs)[source]¶ Bases:
sklearn.base.RegressorMixin
Assemble a proper SVM using sklearn tools regressor
Methods
fit
(descs, target_values, **kwargs)get_params
([deep])predict
(descs)score
(descs, target_values)set_params
(**kwargs)
-
oddt.scoring.models.regressors.
pls
¶ alias of
PLSRegression
-
class
oddt.scoring.models.regressors.
neuralnetwork
(*args, **kwargs)[source]¶ Bases:
sklearn.base.RegressorMixin
Assemble Neural network using sklearn tools plus ffnet wrapper
Methods
fit
(descs, target_values, **kwargs)get_params
([deep])predict
(descs)score
(descs, target_values)set_params
(**kwargs)
-
oddt.scoring.models.regressors.
mlr
¶ alias of
LinearRegression