Name
select_feature_set_trainf_knnT_select_feature_set_trainf_knnSelectFeatureSetTrainfKnnselect_feature_set_trainf_knnSelectFeatureSetTrainfKnnSelectFeatureSetTrainfKnn — Wählt die optimalen Merkmale für ein bestimmtes OCR-Klassifikationsproblem
aus.
Herror select_feature_set_trainf_knn(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 HOCRKnn::SelectFeatureSetTrainfKnn(const HTuple& TrainingFile, const HTuple& FeatureList, const HTuple& SelectionMethod, const HTuple& Width, const HTuple& Height, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* Score)
void SelectFeatureSetTrainfKnn(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 HOCRKnn::SelectFeatureSetTrainfKnn(const HTuple& TrainingFile, const HTuple& FeatureList, const HString& SelectionMethod, Hlong Width, Hlong Height, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* Score)
HTuple HOCRKnn::SelectFeatureSetTrainfKnn(const HString& TrainingFile, const HString& FeatureList, const HString& SelectionMethod, Hlong Width, Hlong Height, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* Score)
HTuple HOCRKnn::SelectFeatureSetTrainfKnn(const char* TrainingFile, const char* FeatureList, const char* SelectionMethod, Hlong Width, Hlong Height, const HTuple& GenParamName, const HTuple& GenParamValue, HTuple* Score)
void HOperatorSetX.SelectFeatureSetTrainfKnn(
[in] VARIANT TrainingFile, [in] VARIANT FeatureList, [in] VARIANT SelectionMethod, [in] VARIANT Width, [in] VARIANT Height, [in] VARIANT GenParamName, [in] VARIANT GenParamValue, [out] VARIANT* OCRHandle, [out] VARIANT* FeatureSet, [out] VARIANT* Score)
VARIANT HOCRKnnX.SelectFeatureSetTrainfKnn(
[in] VARIANT TrainingFile, [in] VARIANT FeatureList, [in] BSTR SelectionMethod, [in] Hlong Width, [in] Hlong Height, [in] VARIANT GenParamName, [in] VARIANT GenParamValue, [out] VARIANT* Score)
static void HOperatorSet.SelectFeatureSetTrainfKnn(HTuple trainingFile, HTuple featureList, HTuple selectionMethod, HTuple width, HTuple height, HTuple genParamName, HTuple genParamValue, out HTuple OCRHandle, out HTuple featureSet, out HTuple score)
HTuple HOCRKnn.SelectFeatureSetTrainfKnn(HTuple trainingFile, HTuple featureList, string selectionMethod, int width, int height, HTuple genParamName, HTuple genParamValue, out HTuple score)
HTuple HOCRKnn.SelectFeatureSetTrainfKnn(string trainingFile, string featureList, string selectionMethod, int width, int height, HTuple genParamName, HTuple genParamValue, out HTuple score)
select_feature_set_trainf_knnselect_feature_set_trainf_knnSelectFeatureSetTrainfKnnselect_feature_set_trainf_knnSelectFeatureSetTrainfKnnSelectFeatureSetTrainfKnn wählt die optimalen Merkmale für
ein bestimmtes OCR-Klassifikationsproblem aus.
Die Daten für das OCR-Klassifikationsproblem werden mit der Trainingsdatei
TrainingFileTrainingFileTrainingFileTrainingFileTrainingFiletrainingFile ausgewählt. Als Klassifikator wird ein
k-Nearest-Neighbor-Klassifikator (kNN) verwendet.
Es wird eine Untermenge aller angegebenen OCR-Merkmale gewählt.
Alle zu untersuchenden Merkmale werden in FeatureListFeatureListFeatureListFeatureListFeatureListfeatureList spezifiziert.
Die Liste der möglichen OCR-Merkmale wird in der Dokumentation von
create_ocr_class_knncreate_ocr_class_knnCreateOcrClassKnncreate_ocr_class_knnCreateOcrClassKnnCreateOcrClassKnn näher erläutert.
Die letztendlich ausgewählte Merkmalsuntermenge wird in FeatureSetFeatureSetFeatureSetFeatureSetFeatureSetfeatureSet
zurückgegeben.
select_feature_set_trainf_knnselect_feature_set_trainf_knnSelectFeatureSetTrainfKnnselect_feature_set_trainf_knnSelectFeatureSetTrainfKnnSelectFeatureSetTrainfKnn ist auf OCR-Klassifikationsprobleme
spezialisiert und unterstützt nur Merkmale, die in der Auswahlliste stehen.
Für andere Merkmale bietet sich somit die Nutzung des generellen Operators
select_feature_set_knnselect_feature_set_knnSelectFeatureSetKnnselect_feature_set_knnSelectFeatureSetKnnSelectFeatureSetKnn an.
Für den Selektionsprozess können in SelectionMethodSelectionMethodSelectionMethodSelectionMethodSelectionMethodselectionMethod zwei
verschiedene Methoden ausgewählt werden: entweder die Greedy-Variante
'greedy'"greedy""greedy""greedy""greedy""greedy" (das momentan erfolgversprechendste Merkmal wird
zur Auswahl hinzugefügt) oder die dynamisch oszillierende Suche
'greedy_oscillating'"greedy_oscillating""greedy_oscillating""greedy_oscillating""greedy_oscillating""greedy_oscillating" (Das momentan erfolgversprechendste Merkmal
wird zur Auswahl hinzugefügt. Danach wird getestet ob eines
der hinzugefügten Merkmale entbehrlich ist.).
Während 'greedy'"greedy""greedy""greedy""greedy""greedy" schneller terminiert,
kann 'greedy_oscillating'"greedy_oscillating""greedy_oscillating""greedy_oscillating""greedy_oscillating""greedy_oscillating" bessere Ergebnisse erzielen wenn
viele Trainingsdaten vorliegen.
Als Optimierungskriterium dient die Klassifikationsrate, die mit einem
zwei-fachen Kreuzvalidierungsverfahren ermittelt wird. Die beste erreichte
Klassifikationsrate wird in ScoreScoreScoreScoreScorescore zurückgegeben.
OCRHandleOCRHandleOCRHandleOCRHandleOCRHandleOCRHandle gibt einen Klassifikator zurück, der mit der
entsprechenden Featureauswahl parametrisiert und trainiert wurde.
Mit Hilfe der Parameter GenParamNameGenParamNameGenParamNameGenParamNameGenParamNamegenParamName und GenParamValueGenParamValueGenParamValueGenParamValueGenParamValuegenParamValue
können die folgenden Werte gesetzt werden:
- 'num_neighbors'"num_neighbors""num_neighbors""num_neighbors""num_neighbors""num_neighbors":
-
Anzahl Nachbarn die ermittelt werden,
das Erhöhen dieses Wertes führt zu besseren Ergebnissen bei
längerer Laufzeit.
Possible values: '1'"1""1""1""1""1", '2'"2""2""2""2""2", '5'"5""5""5""5""5",
'10'"10""10""10""10""10"
Default value: '1'"1""1""1""1""1"
- 'num_trees'"num_trees""num_trees""num_trees""num_trees""num_trees":
-
die Anzahl an Suchbäumen im k-NN
Possible values: '1'"1""1""1""1""1", '4'"4""4""4""4""4", '10'"10""10""10""10""10"
Default Value: '4'"4""4""4""4""4"
Die Laufzeit dieses Operators kann mit größeren Datensätzen und einer
längeren Merkmalsliste unter Umständen sehr lange sein.
Es ist zu beachten, dass dieser Operator nicht aufgerufen werden sollte,
wenn für das Training nur ein kleiner Datensatz verfügbar ist.
Auf Grund des Risikos der Überanpassung kann der Operator
select_feature_set_trainf_knnselect_feature_set_trainf_knnSelectFeatureSetTrainfKnnselect_feature_set_trainf_knnSelectFeatureSetTrainfKnnSelectFeatureSetTrainfKnn zwar einerseits einen Klassifikator
mit sehr hohem Score liefern. Andererseits weist der Klassifikator
jedoch eine schlechte Erkennungsrate auf, wenn dieser getestet wird.
- Multithreading-Typ: reentrant (läuft parallel zu nicht-exklusiven Operatoren).
- Multithreading-Bereich: global (kann von jedem Thread aufgerufen werden).
- Automatisch parallelisiert auf interner Datenebene.
Dieser Operator liefert ein Handle zurück. Es ist zu beachten, dass der Zustand einer Instanz dieses Handletyps durch bestimmte Operatoren geändert werden kann, obwohl das Handle als Eingabeparameter in diesen Operatoren verwendet wird.
Namen der Trainingsdateien.
Defaultwert:
''
""
""
""
""
""
Dateiendung: .trf, .otr
Merkmale, die zur Klassifikation verwendet werden können.
Defaultwert:
['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"]
Werteliste: '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"
Die Methode zur Auswahl der Merkmale.
Defaultwert:
'greedy'
"greedy"
"greedy"
"greedy"
"greedy"
"greedy"
Werteliste: 'greedy'"greedy""greedy""greedy""greedy""greedy", 'greedy_oscillating'"greedy_oscillating""greedy_oscillating""greedy_oscillating""greedy_oscillating""greedy_oscillating"
Breite des Rechtecks, auf die die Grauwerte des
segmentierten Zeichens skaliert werden.
Defaultwert: 15
Höhe des Rechtecks, auf die die Grauwerte des
segmentierten Zeichens skaliert werden.
Defaultwert: 16
Namen von (optionalen) Parametern für
die Steuerung des Verhaltens verwendeten
des k-NN Klassifikators.
Defaultwert: []
Werteliste: 'num_neighbors'"num_neighbors""num_neighbors""num_neighbors""num_neighbors""num_neighbors"
Die zu den optionalen generischen
Parametern gehörenden Werte.
Defaultwert: []
Wertevorschläge: 1, 2, 3
Ein trainierter k-NN Klassifikator.
Die ausgewählten Merkmale.
Die Klassifikationsrate die mit dem ausgewählten
Merkmalssatz erreicht wurde.
Sind die Parameterwerte korrekt, dann liefert
select_feature_set_trainf_knnselect_feature_set_trainf_knnSelectFeatureSetTrainfKnnselect_feature_set_trainf_knnSelectFeatureSetTrainfKnnSelectFeatureSetTrainfKnn den Wert 2 (H_MSG_TRUE). Gegebenenfalls wird
eine Fehlerbehandlung durchgeführt.
select_feature_set_trainf_svmselect_feature_set_trainf_svmSelectFeatureSetTrainfSvmselect_feature_set_trainf_svmSelectFeatureSetTrainfSvmSelectFeatureSetTrainfSvm,
select_feature_set_trainf_mlpselect_feature_set_trainf_mlpSelectFeatureSetTrainfMlpselect_feature_set_trainf_mlpSelectFeatureSetTrainfMlpSelectFeatureSetTrainfMlp
select_feature_set_knnselect_feature_set_knnSelectFeatureSetKnnselect_feature_set_knnSelectFeatureSetKnnSelectFeatureSetKnn
OCR/OCV