set_params_class_knnT_set_params_class_knnSetParamsClassKnnSetParamsClassKnnset_params_class_knn (算子)

名称

set_params_class_knnT_set_params_class_knnSetParamsClassKnnSetParamsClassKnnset_params_class_knn — 设置 k-NN 分类的参数。

签名

描述

set_params_class_knnset_params_class_knnSetParamsClassKnnSetParamsClassKnnSetParamsClassKnnset_params_class_knn sets parameters for the classification of the k-nearest neighbors (k-NN) classifier KNNHandleKNNHandleKNNHandleKNNHandleKNNHandleknnhandle. It controls the behavior of classify_class_knnclassify_class_knnClassifyClassKnnClassifyClassKnnClassifyClassKnnclassify_class_knn。

The value of 'k'"k""k""k""k""k" can be set via GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name and GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value. Increasing 'k'"k""k""k""k""k" also increases the accuracy of the resulting neighbors and increases the run time.

The results can either be the determined class of the feature vector or the indices of the nearest neighbors. The result behavior can be selected with set_params_class_knnset_params_class_knnSetParamsClassKnnSetParamsClassKnnSetParamsClassKnnset_params_class_knn via the generic parameters 'method'"method""method""method""method""method" and 'max_num_classes'"max_num_classes""max_num_classes""max_num_classes""max_num_classes""max_num_classes"：

'classes_distance'"classes_distance""classes_distance""classes_distance""classes_distance""classes_distance"：

returns the nearest samples for each of maximally 'max_num_classes'"max_num_classes""max_num_classes""max_num_classes""max_num_classes""max_num_classes" different classes, if they have a representative in the nearest 'k'"k""k""k""k""k" neighbors. The results are classes sorted by their minimal distance. There is no efficient way to determine in a k-NN-tree the nearest neighbor for exactly 'max_num_classes'"max_num_classes""max_num_classes""max_num_classes""max_num_classes""max_num_classes" classes.

'classes_frequency'"classes_frequency""classes_frequency""classes_frequency""classes_frequency""classes_frequency"：

counts the occurrences of certain classes among the nearest 'k'"k""k""k""k""k" neighbors and returns the occurrent classes sorted by their relative frequency that is returned, too. Again, maximally 'max_num_classes'"max_num_classes""max_num_classes""max_num_classes""max_num_classes""max_num_classes" values are returned.

'classes_weighted_frequencies'"classes_weighted_frequencies""classes_weighted_frequencies""classes_weighted_frequencies""classes_weighted_frequencies""classes_weighted_frequencies"：

counts the occurrences of certain classes among the nearest 'k'"k""k""k""k""k" neighbors and returns the occurrent classes sorted by their relative frequency weighted with the average distance that is returned, too. Again, maximally 'max_num_classes'"max_num_classes""max_num_classes""max_num_classes""max_num_classes""max_num_classes" values are returned.

'neighbors_distance'"neighbors_distance""neighbors_distance""neighbors_distance""neighbors_distance""neighbors_distance"：

returns the indices of the nearest 'k'"k""k""k""k""k" neighbors and the distances.

The default behavior is 'classes_distance'"classes_distance""classes_distance""classes_distance""classes_distance""classes_distance".

The option 'num_checks'"num_checks""num_checks""num_checks""num_checks""num_checks" allows to set the number of maximal runs through the trees. The parameter has to be positive and the default value is 32. The higher this value is, the more accurate the results will be. As a trade-off, the running time will also be higher. Setting this parameter to 0 triggers an exact search.

The option 'epsilon'"epsilon""epsilon""epsilon""epsilon""epsilon" allows to set a stop criteria if the value is increased from the default value 0.0. The higher the value is set, the less accurate results of the estimated neighbors can be expected, while it might speed up the search.

执行信息

• 多线程类型：可重入（与非独占算子并行运行）。
• 多线程作用域：全局（可从任何线程调用）。
• 未采用并行化处理。

此算子修改后续输入参数的状态：

• KNNHandleKNNHandleKNNHandleKNNHandleKNNHandleknnhandle

在执行此算子时，若该参数值需在多个线程间使用，则必须对其访问进行同步。

参数

结果

如果参数有效，算子 set_params_class_knnset_params_class_knnSetParamsClassKnnSetParamsClassKnnSetParamsClassKnnset_params_class_knn 返回值 2 ( H_MSG_TRUE )。如有必要，则抛出异常。

可能的前趋

train_class_knntrain_class_knnTrainClassKnnTrainClassKnnTrainClassKnntrain_class_knn, read_class_knnread_class_knnReadClassKnnReadClassKnnReadClassKnnread_class_knn

可能的后继

classify_class_knnclassify_class_knnClassifyClassKnnClassifyClassKnnClassifyClassKnnclassify_class_knn

另见

create_class_knncreate_class_knnCreateClassKnnCreateClassKnnCreateClassKnncreate_class_knn, read_class_knnread_class_knnReadClassKnnReadClassKnnReadClassKnnread_class_knn, get_params_class_knnget_params_class_knnGetParamsClassKnnGetParamsClassKnnGetParamsClassKnnget_params_class_knn

参考文献

Marius Muja, David G. Lowe: “Fast Approximate Nearest Neighbors with Automatic Algorithm Configuration”; International Conference on Computer Vision Theory and Applications (VISAPP 09); 2009.

模块

基础