sklearn_pmml_model.neighbors
#
The sklearn.neighbors
module implements the k-nearest neighbors
algorithm.
Submodules#
Package Contents#
Classes#
Classifier implementing the k-nearest neighbors vote. |
|
Regression based on k-nearest neighbors. |
- class sklearn_pmml_model.neighbors.PMMLKNeighborsClassifier(pmml, n_jobs=None)#
Bases:
sklearn_pmml_model.base.PMMLBaseClassifier
,sklearn_pmml_model.neighbors._base.PMMLBaseKNN
,sklearn.neighbors.KNeighborsClassifier
Classifier implementing the k-nearest neighbors vote.
- Parameters:
- pmmlstr, object
Filename or file object containing PMML data.
- n_jobsint, default=None
The number of parallel jobs to run for neighbors search.
None
means 1 unless in ajoblib.parallel_backend
context.-1
means using all processors. See Glossary for more details. Doesn’t affectfit()
method.
Notes
Specification: http://dmg.org/pmml/v4-3/KNN.html
- fit(x, y)#
Not supported: PMML models are already fitted.
- _more_tags()#
- class sklearn_pmml_model.neighbors.PMMLKNeighborsRegressor(pmml, n_jobs=None)#
Bases:
sklearn_pmml_model.base.PMMLBaseRegressor
,sklearn_pmml_model.neighbors._base.PMMLBaseKNN
,sklearn.neighbors.KNeighborsRegressor
Regression based on k-nearest neighbors.
The target is predicted by local interpolation of the targets associated of the nearest neighbors in the training set.
- Parameters:
- pmmlstr, object
Filename or file object containing PMML data.
- n_jobsint, default=None
The number of parallel jobs to run for neighbors search.
None
means 1 unless in ajoblib.parallel_backend
context.-1
means using all processors. See Glossary for more details. Doesn’t affectfit()
method.
Notes
Specification: http://dmg.org/pmml/v4-3/KNN.html
- fit(x, y)#
Not supported: PMML models are already fitted.
- _more_tags()#