get_params_class_knnT_get_params_class_knnGetParamsClassKnnGetParamsClassKnnget_params_class_knn (Operator)
Name
get_params_class_knnT_get_params_class_knnGetParamsClassKnnGetParamsClassKnnget_params_class_knn — Get parameters of a k-NN classification.
Signature
Description
get_params_class_knnget_params_class_knnGetParamsClassKnnGetParamsClassKnnGetParamsClassKnnget_params_class_knn gets parameters of
the k-NN referred by KNNHandleKNNHandleKNNHandleKNNHandleKNNHandleknnhandle. The possible entries in
GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name are:
- 'method'"method""method""method""method""method":
Retrieve the currently selected method
for determining the result of classify_class_knnclassify_class_knnClassifyClassKnnClassifyClassKnnClassifyClassKnnclassify_class_knn.
The result can be 'classes_distance'"classes_distance""classes_distance""classes_distance""classes_distance""classes_distance",
'classes_frequency'"classes_frequency""classes_frequency""classes_frequency""classes_frequency""classes_frequency", 'classes_weighted_frequencies'"classes_weighted_frequencies""classes_weighted_frequencies""classes_weighted_frequencies""classes_weighted_frequencies""classes_weighted_frequencies"
or 'neighbors_distance'"neighbors_distance""neighbors_distance""neighbors_distance""neighbors_distance""neighbors_distance".
- 'k'"k""k""k""k""k":
The number of nearest neighbors that is considered
to determine the results.
- 'max_num_classes'"max_num_classes""max_num_classes""max_num_classes""max_num_classes""max_num_classes":
The maximum number of classes that are
returned. This parameter is ignored in case the method
'neighbors_distance'"neighbors_distance""neighbors_distance""neighbors_distance""neighbors_distance""neighbors_distance" is selected.
- 'num_checks'"num_checks""num_checks""num_checks""num_checks""num_checks":
Defines the maximum number of runs through
the trees.
- 'epsilon'"epsilon""epsilon""epsilon""epsilon""epsilon":
A parameter to lower the accuracy in
the tree to gain speed.
Execution Information
- Multithreading type: reentrant (runs in parallel with non-exclusive operators).
- Multithreading scope: global (may be called from any thread).
- Processed without parallelization.
Parameters
KNNHandleKNNHandleKNNHandleKNNHandleKNNHandleknnhandle (input_control) class_knn → HClassKnn, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)
Handle of the k-NN classifier.
GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name (input_control) string-array → HTupleSequence[str]HTupleHtuple (string) (string) (HString) (char*)
Names of the parameters that can be read
from the k-NN classifier.
Default value:
['method','k']
["method","k"]
["method","k"]
["method","k"]
["method","k"]
["method","k"]
List of values: 'epsilon'"epsilon""epsilon""epsilon""epsilon""epsilon", 'k'"k""k""k""k""k", 'method'"method""method""method""method""method", 'num_checks'"num_checks""num_checks""num_checks""num_checks""num_checks"
GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value (output_control) number-array → HTupleSequence[Union[int, float, str]]HTupleHtuple (integer / real / string) (int / long / double / string) (Hlong / double / HString) (Hlong / double / char*)
Values of the selected parameters.
Result
If the parameters are valid, the operator get_params_class_knnget_params_class_knnGetParamsClassKnnGetParamsClassKnnGetParamsClassKnnget_params_class_knn
returns the value 2 (H_MSG_TRUE). If necessary, an exception is raised.
Possible Predecessors
train_class_knntrain_class_knnTrainClassKnnTrainClassKnnTrainClassKnntrain_class_knn,
read_class_knnread_class_knnReadClassKnnReadClassKnnReadClassKnnread_class_knn
Possible Successors
classify_class_knnclassify_class_knnClassifyClassKnnClassifyClassKnnClassifyClassKnnclassify_class_knn
See also
create_class_knncreate_class_knnCreateClassKnnCreateClassKnnCreateClassKnncreate_class_knn,
read_class_knnread_class_knnReadClassKnnReadClassKnnReadClassKnnread_class_knn
References
Marius Muja, David G. Lowe: “Fast Approximate Nearest Neighbors with
Automatic Algorithm Configuration”;
International Conference on Computer Vision Theory
and Applications (VISAPP 09); 2009.
Module
Foundation