Operator Reference
reduce_ocr_class_svm (Operator)
reduce_ocr_class_svm
— Approximate a trained SVM-based OCR classifier by a reduced SVM.
Signature
reduce_ocr_class_svm( : : OCRHandle, Method, MinRemainingSV, MaxError : OCRHandleReduced)
Description
reduce_ocr_class_svm
reduces the classification time of an
SVM based OCR classifier OCRHandle
by returning a reduced
copy of it in OCRHandleReduced
. The parameters
Method
, MinRemainingSV
and MaxError
have
the same meaning as in reduce_class_svm
and are described
there. Please note that classification time can also be
significantly reduced with a preprocessing step in
create_ocr_class_svm
, which possibly introduces less
errors.
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
OCRHandle
(input_control) ocr_svm →
(handle)
Original handle of SVM-based OCR-classifier.
Method
(input_control) string →
(string)
Type of postprocessing to reduce number of SVs.
Default: 'bottom_up'
List of values: 'bottom_up'
MinRemainingSV
(input_control) integer →
(integer)
Minimum number of remaining SVs.
Default: 2
Suggested values: 2, 3, 4, 5, 7, 10, 15, 20, 30, 50
Restriction:
MinRemainingSV >= 2
MaxError
(input_control) real →
(real)
Maximum allowed error of reduction.
Default: 0.001
Suggested values: 0.0001, 0.0002, 0.0005, 0.001, 0.002, 0.005, 0.01, 0.02, 0.05
Restriction:
MaxError > 0.0
OCRHandleReduced
(output_control) ocr_svm →
(handle)
SVMHandle of reduced OCR classifier.
Result
If the parameters are valid the operator
reduce_ocr_class_svm
returns the value 2 (
H_MSG_TRUE)
. If necessary,
an exception is raised.
Possible Predecessors
trainf_ocr_class_svm
,
get_support_vector_num_ocr_class_svm
Possible Successors
do_ocr_single_class_svm
,
do_ocr_multi_class_svm
,
get_support_vector_ocr_class_svm
,
get_support_vector_num_ocr_class_svm
See also
References
Bernhard Schölkopf, Alexander J.Smola: “Learning with Kernels”; The MIT Press, London; 1999.
Module
OCR/OCV