SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping h: X--> Y using labeled training examples (x1,y1), ..., (xn,yn). Unlike regular SVMs, however, which consider only univariate predictions like in classification and regression, SVMstruct can predict complex objects y like trees, sequences, or sets. Examples of problems with complex outputs are natural language parsing, sequence alignment in protein homology detection, and markov models for part-of-speech tagging. The SVMstruct algorithm can also be used for linear-time training of binary and multi-class SVMs under the linear kernel.

LICENSE.txt
Makefile
svm_light
.........\kernel.h
.........\LICENSE.txt
.........\Makefile
.........\svm_classify.c
.........\svm_common.c
.........\svm_common.h
.........\svm_hideo.c
.........\svm_learn.c
.........\svm_learn.h
.........\svm_learn_main.c
.........\svm_loqo.c
svm_struct
..........\Makefile
..........\svm_struct_classify.c
..........\svm_struct_common.c
..........\svm_struct_common.h
..........\svm_struct_learn.c
..........\svm_struct_learn.h
..........\svm_struct_main.c
svm_struct_api.c
svm_struct_api.h
svm_struct_api_types.h
svm_struct_learn_custom.c

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