select_feature_set_trainf_mlpT_select_feature_set_trainf_mlpSelectFeatureSetTrainfMlpSelectFeatureSetTrainfMlpselect_feature_set_trainf_mlp (算子)

名称

select_feature_set_trainf_mlpT_select_feature_set_trainf_mlpSelectFeatureSetTrainfMlpSelectFeatureSetTrainfMlpselect_feature_set_trainf_mlp — 选择最佳的特征组合来对 OCR 数据进行分类。

签名

select_feature_set_trainf_mlp( : : TrainingFile, FeatureList, SelectionMethod, Width, Height, GenParamName, GenParamValue : OCRHandle, FeatureSet, Score)

Herror T_select_feature_set_trainf_mlp(const Htuple TrainingFile, const Htuple FeatureList, const Htuple SelectionMethod, const Htuple Width, const Htuple Height, const Htuple GenParamName, const Htuple GenParamValue, Htuple* OCRHandle, Htuple* FeatureSet, Htuple* Score)

void SelectFeatureSetTrainfMlp(const HTuple& TrainingFile, const HTuple& FeatureList, const HTuple& SelectionMethod, const HTuple& Width, const HTuple& Height, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* OCRHandle, HTuple* FeatureSet, HTuple* Score)

HTuple HOCRMlp::SelectFeatureSetTrainfMlp(const HTuple& TrainingFile, const HTuple& FeatureList, const HString& SelectionMethod, Hlong Width, Hlong Height, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* Score)

HTuple HOCRMlp::SelectFeatureSetTrainfMlp(const HString& TrainingFile, const HString& FeatureList, const HString& SelectionMethod, Hlong Width, Hlong Height, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* Score)

HTuple HOCRMlp::SelectFeatureSetTrainfMlp(const char* TrainingFile, const char* FeatureList, const char* SelectionMethod, Hlong Width, Hlong Height, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* Score)

HTuple HOCRMlp::SelectFeatureSetTrainfMlp(const wchar_t* TrainingFile, const wchar_t* FeatureList, const wchar_t* SelectionMethod, Hlong Width, Hlong Height, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* Score)   ( Windows only)

static void HOperatorSet.SelectFeatureSetTrainfMlp(HTuple trainingFile, HTuple featureList, HTuple selectionMethod, HTuple width, HTuple height, HTuple genParamName, HTuple genParamValue, out HTuple OCRHandle, out HTuple featureSet, out HTuple score)

HTuple HOCRMlp.SelectFeatureSetTrainfMlp(HTuple trainingFile, HTuple featureList, string selectionMethod, int width, int height, HTuple genParamName, HTuple genParamValue, out HTuple score)

HTuple HOCRMlp.SelectFeatureSetTrainfMlp(string trainingFile, string featureList, string selectionMethod, int width, int height, HTuple genParamName, HTuple genParamValue, out HTuple score)

def select_feature_set_trainf_mlp(training_file: MaybeSequence[str], feature_list: MaybeSequence[str], selection_method: str, width: int, height: int, gen_param_name: Sequence[str], gen_param_value: Sequence[Union[int, str, float]]) -> Tuple[HHandle, Sequence[str], Sequence[float]]

描述

select_feature_set_trainf_mlpselect_feature_set_trainf_mlpSelectFeatureSetTrainfMlpSelectFeatureSetTrainfMlpSelectFeatureSetTrainfMlpselect_feature_set_trainf_mlp selects an optimal combination of features, to classify the OCR data given in the training file TrainingFileTrainingFileTrainingFileTrainingFiletrainingFiletraining_file with a multilayer perceptron, for details see create_ocr_class_mlpcreate_ocr_class_mlpCreateOcrClassMlpCreateOcrClassMlpCreateOcrClassMlpcreate_ocr_class_mlp

Possible features are all OCR features listed and explained in create_ocr_class_mlpcreate_ocr_class_mlpCreateOcrClassMlpCreateOcrClassMlpCreateOcrClassMlpcreate_ocr_class_mlp。All candidates which should be tested can be specified in FeatureListFeatureListFeatureListFeatureListfeatureListfeature_list. A subset of these features is returned as selected features in FeatureSetFeatureSetFeatureSetFeatureSetfeatureSetfeature_set

select_feature_set_trainf_mlpselect_feature_set_trainf_mlpSelectFeatureSetTrainfMlpSelectFeatureSetTrainfMlpSelectFeatureSetTrainfMlpselect_feature_set_trainf_mlp is specialized on OCR problems and only supports the features in the list mentioned before. In order to use other features, please use the more general operator select_feature_set_mlpselect_feature_set_mlpSelectFeatureSetMlpSelectFeatureSetMlpSelectFeatureSetMlpselect_feature_set_mlp

The selection method SelectionMethodSelectionMethodSelectionMethodSelectionMethodselectionMethodselection_method is either a greedy search 'greedy'"greedy""greedy""greedy""greedy""greedy" (iteratively add the feature with highest gain) or the dynamically oscillating search 'greedy_oscillating'"greedy_oscillating""greedy_oscillating""greedy_oscillating""greedy_oscillating""greedy_oscillating" (add the feature with highest gain and test then if any of the already added features can be left out without great loss). The method 'greedy'"greedy""greedy""greedy""greedy""greedy" is generally preferable, since it is faster. Only in cases when a large training set is available the method 'greedy_oscillating'"greedy_oscillating""greedy_oscillating""greedy_oscillating""greedy_oscillating""greedy_oscillating" might return better results.

The optimization criterion is the classification rate of a two-fold cross-validation of the training data. The best achieved value is returned in ScoreScoreScoreScorescorescore

The parameters GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name and GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value allow to adapt the setting of the number of hidden neurons in the MLP with 'num_hidden'"num_hidden""num_hidden""num_hidden""num_hidden""num_hidden". The default value is 80, a higher value leads to longer training times but might lead to a more expressive classifier.

注意

This operator may take considerable time, depending on the size of the data set in the training file, and the number of features.

Please note, that this operator should not be called, if only a small set of training data is available. Due to the risk of overfitting the operator select_feature_set_trainf_mlpselect_feature_set_trainf_mlpSelectFeatureSetTrainfMlpSelectFeatureSetTrainfMlpSelectFeatureSetTrainfMlpselect_feature_set_trainf_mlp may deliver a classifier with a very high score. However, the classifier may perform poorly when tested.

执行信息

此算子返回一个句柄。请注意,即使该句柄被用作特定算子的输入参数,这些算子仍可能改变此句柄类型的实例状态。

参数

TrainingFileTrainingFileTrainingFileTrainingFiletrainingFiletraining_file (输入控制)  filename.read(-array) HTupleMaybeSequence[str]HTupleHtuple (string) (string) (HString) (char*)

Names of the training files.

默认值: '' "" "" "" "" ""

File extension: .trf, .otr

FeatureListFeatureListFeatureListFeatureListfeatureListfeature_list (输入控制)  string(-array) HTupleMaybeSequence[str]HTupleHtuple (string) (string) (HString) (char*)

List of features that should be considered for selection.

默认值: ['zoom_factor','ratio','width','height','foreground','foreground_grid_9','foreground_grid_16','anisometry','compactness','convexity','moments_region_2nd_invar','moments_region_2nd_rel_invar','moments_region_3rd_invar','moments_central','phi','num_connect','num_holes','projection_horizontal','projection_vertical','projection_horizontal_invar','projection_vertical_invar','chord_histo','num_runs','pixel','pixel_invar','pixel_binary','gradient_8dir','cooc','moments_gray_plane'] ["zoom_factor","ratio","width","height","foreground","foreground_grid_9","foreground_grid_16","anisometry","compactness","convexity","moments_region_2nd_invar","moments_region_2nd_rel_invar","moments_region_3rd_invar","moments_central","phi","num_connect","num_holes","projection_horizontal","projection_vertical","projection_horizontal_invar","projection_vertical_invar","chord_histo","num_runs","pixel","pixel_invar","pixel_binary","gradient_8dir","cooc","moments_gray_plane"] ["zoom_factor","ratio","width","height","foreground","foreground_grid_9","foreground_grid_16","anisometry","compactness","convexity","moments_region_2nd_invar","moments_region_2nd_rel_invar","moments_region_3rd_invar","moments_central","phi","num_connect","num_holes","projection_horizontal","projection_vertical","projection_horizontal_invar","projection_vertical_invar","chord_histo","num_runs","pixel","pixel_invar","pixel_binary","gradient_8dir","cooc","moments_gray_plane"] ["zoom_factor","ratio","width","height","foreground","foreground_grid_9","foreground_grid_16","anisometry","compactness","convexity","moments_region_2nd_invar","moments_region_2nd_rel_invar","moments_region_3rd_invar","moments_central","phi","num_connect","num_holes","projection_horizontal","projection_vertical","projection_horizontal_invar","projection_vertical_invar","chord_histo","num_runs","pixel","pixel_invar","pixel_binary","gradient_8dir","cooc","moments_gray_plane"] ["zoom_factor","ratio","width","height","foreground","foreground_grid_9","foreground_grid_16","anisometry","compactness","convexity","moments_region_2nd_invar","moments_region_2nd_rel_invar","moments_region_3rd_invar","moments_central","phi","num_connect","num_holes","projection_horizontal","projection_vertical","projection_horizontal_invar","projection_vertical_invar","chord_histo","num_runs","pixel","pixel_invar","pixel_binary","gradient_8dir","cooc","moments_gray_plane"] ["zoom_factor","ratio","width","height","foreground","foreground_grid_9","foreground_grid_16","anisometry","compactness","convexity","moments_region_2nd_invar","moments_region_2nd_rel_invar","moments_region_3rd_invar","moments_central","phi","num_connect","num_holes","projection_horizontal","projection_vertical","projection_horizontal_invar","projection_vertical_invar","chord_histo","num_runs","pixel","pixel_invar","pixel_binary","gradient_8dir","cooc","moments_gray_plane"]

值列表: 'anisometry'"anisometry""anisometry""anisometry""anisometry""anisometry", 'chord_histo'"chord_histo""chord_histo""chord_histo""chord_histo""chord_histo", 'compactness'"compactness""compactness""compactness""compactness""compactness", 'convexity'"convexity""convexity""convexity""convexity""convexity", 'cooc'"cooc""cooc""cooc""cooc""cooc", 'default'"default""default""default""default""default", 'foreground'"foreground""foreground""foreground""foreground""foreground", 'foreground_grid_16'"foreground_grid_16""foreground_grid_16""foreground_grid_16""foreground_grid_16""foreground_grid_16", 'foreground_grid_9'"foreground_grid_9""foreground_grid_9""foreground_grid_9""foreground_grid_9""foreground_grid_9", 'gradient_8dir'"gradient_8dir""gradient_8dir""gradient_8dir""gradient_8dir""gradient_8dir", 'height'"height""height""height""height""height", 'moments_central'"moments_central""moments_central""moments_central""moments_central""moments_central", 'moments_gray_plane'"moments_gray_plane""moments_gray_plane""moments_gray_plane""moments_gray_plane""moments_gray_plane", 'moments_region_2nd_invar'"moments_region_2nd_invar""moments_region_2nd_invar""moments_region_2nd_invar""moments_region_2nd_invar""moments_region_2nd_invar", 'moments_region_2nd_rel_invar'"moments_region_2nd_rel_invar""moments_region_2nd_rel_invar""moments_region_2nd_rel_invar""moments_region_2nd_rel_invar""moments_region_2nd_rel_invar", 'moments_region_3rd_invar'"moments_region_3rd_invar""moments_region_3rd_invar""moments_region_3rd_invar""moments_region_3rd_invar""moments_region_3rd_invar", 'num_connect'"num_connect""num_connect""num_connect""num_connect""num_connect", 'num_holes'"num_holes""num_holes""num_holes""num_holes""num_holes", 'num_runs'"num_runs""num_runs""num_runs""num_runs""num_runs", 'phi'"phi""phi""phi""phi""phi", 'pixel'"pixel""pixel""pixel""pixel""pixel", 'pixel_binary'"pixel_binary""pixel_binary""pixel_binary""pixel_binary""pixel_binary", 'pixel_invar'"pixel_invar""pixel_invar""pixel_invar""pixel_invar""pixel_invar", 'projection_horizontal'"projection_horizontal""projection_horizontal""projection_horizontal""projection_horizontal""projection_horizontal", 'projection_horizontal_invar'"projection_horizontal_invar""projection_horizontal_invar""projection_horizontal_invar""projection_horizontal_invar""projection_horizontal_invar", 'projection_vertical'"projection_vertical""projection_vertical""projection_vertical""projection_vertical""projection_vertical", 'projection_vertical_invar'"projection_vertical_invar""projection_vertical_invar""projection_vertical_invar""projection_vertical_invar""projection_vertical_invar", 'ratio'"ratio""ratio""ratio""ratio""ratio", 'width'"width""width""width""width""width", 'zoom_factor'"zoom_factor""zoom_factor""zoom_factor""zoom_factor""zoom_factor"

SelectionMethodSelectionMethodSelectionMethodSelectionMethodselectionMethodselection_method (输入控制)  string HTuplestrHTupleHtuple (string) (string) (HString) (char*)

Method to perform the selection.

默认值: 'greedy' "greedy" "greedy" "greedy" "greedy" "greedy"

值列表: 'greedy'"greedy""greedy""greedy""greedy""greedy", 'greedy_oscillating'"greedy_oscillating""greedy_oscillating""greedy_oscillating""greedy_oscillating""greedy_oscillating"

WidthWidthWidthWidthwidthwidth (输入控制)  integer HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Width of the rectangle to which the gray values of the segmented character are zoomed.

默认值: 15

HeightHeightHeightHeightheightheight (输入控制)  integer HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Height of the rectangle to which the gray values of the segmented character are zoomed.

默认值: 16

GenParamNameGenParamNameGenParamNameGenParamNamegenParamNamegen_param_name (输入控制)  string-array HTupleSequence[str]HTupleHtuple (string) (string) (HString) (char*)

Names of generic parameters to configure the selection process and the classifier.

默认值: []

值列表: 'nu'"nu""nu""nu""nu""nu"

GenParamValueGenParamValueGenParamValueGenParamValuegenParamValuegen_param_value (输入控制)  number-array HTupleSequence[Union[int, str, float]]HTupleHtuple (real / integer / string) (double / int / long / string) (double / Hlong / HString) (double / Hlong / char*)

Values of generic parameters to configure the selection process and the classifier.

默认值: []

建议值: '0.1'"0.1""0.1""0.1""0.1""0.1"

OCRHandleOCRHandleOCRHandleOCRHandleOCRHandleocrhandle (输出控制)  ocr_mlp HOCRMlp, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

Trained OCR-MLP classifier.

FeatureSetFeatureSetFeatureSetFeatureSetfeatureSetfeature_set (输出控制)  string-array HTupleSequence[str]HTupleHtuple (string) (string) (HString) (char*)

Selected feature set, contains only entries from FeatureListFeatureListFeatureListFeatureListfeatureListfeature_list

ScoreScoreScoreScorescorescore (输出控制)  real-array HTupleSequence[float]HTupleHtuple (real) (double) (double) (double)

Achieved score using tow-fold cross-validation.

结果

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

替代

select_feature_set_trainf_svmselect_feature_set_trainf_svmSelectFeatureSetTrainfSvmSelectFeatureSetTrainfSvmSelectFeatureSetTrainfSvmselect_feature_set_trainf_svm, select_feature_set_trainf_knnselect_feature_set_trainf_knnSelectFeatureSetTrainfKnnSelectFeatureSetTrainfKnnSelectFeatureSetTrainfKnnselect_feature_set_trainf_knn

另见

select_feature_set_trainf_mlp_protectedselect_feature_set_trainf_mlp_protectedSelectFeatureSetTrainfMlpProtectedSelectFeatureSetTrainfMlpProtectedSelectFeatureSetTrainfMlpProtectedselect_feature_set_trainf_mlp_protected, select_feature_set_mlpselect_feature_set_mlpSelectFeatureSetMlpSelectFeatureSetMlpSelectFeatureSetMlpselect_feature_set_mlp

模块

光学字符识别/光学字符验证