文件名称:jsgd-61
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- 上传时间：2013-09-03
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文件大小：171.17kb
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该代码采用matlab和C混合编写，是采用随机梯度的方法训练线性分类器，它可用于数据、图像等的多类分类情况。参考论文：Good Practice in Large-Scale Learning for Image Classification-This a Stochastic Gradient Descent algorithm used to train linear multiclass classifiers. It is biased towards large classification problems (many classes, many examples, high dimensional data).
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下载文件列表
jsgd-61/
jsgd-61/c/
jsgd-61/c/jsgd.c
jsgd-61/c/jsgd.h
jsgd-61/c/x_matrix.c
jsgd-61/c/x_matrix.h
jsgd-61/Makefile
jsgd-61/matlab/
jsgd-61/matlab/jsgd_train.c
jsgd-61/matlab/jsgd_train.m
jsgd-61/matlab/jsgd_train.mexa64
jsgd-61/matlab/pq_decode.m
jsgd-61/matlab/test_jsgd_train.m
jsgd-61/matlab/test_pq_encoded.m
jsgd-61/python/
jsgd-61/python/crossval.py
jsgd-61/python/example_BOW.py
jsgd-61/python/jsgd.py
jsgd-61/python/jsgd_wrap.py
jsgd-61/python/jsgd_wrap.swg
jsgd-61/python/jsgd_wrap_wrap.c
jsgd-61/python/test_jsgd_train.py
jsgd-61/README
jsgd-61/ref/
jsgd-61/ref/generate_toy_data.m
jsgd-61/ref/plot_with_labels.m
jsgd-61/ref/read_svmlight.m
jsgd-61/ref/sgd_simple.m
jsgd-61/ref/sgd_simple_toy_data.m
jsgd-61/ref/write_svmlight.m
jsgd-61/c/
jsgd-61/c/jsgd.c
jsgd-61/c/jsgd.h
jsgd-61/c/x_matrix.c
jsgd-61/c/x_matrix.h
jsgd-61/Makefile
jsgd-61/matlab/
jsgd-61/matlab/jsgd_train.c
jsgd-61/matlab/jsgd_train.m
jsgd-61/matlab/jsgd_train.mexa64
jsgd-61/matlab/pq_decode.m
jsgd-61/matlab/test_jsgd_train.m
jsgd-61/matlab/test_pq_encoded.m
jsgd-61/python/
jsgd-61/python/crossval.py
jsgd-61/python/example_BOW.py
jsgd-61/python/jsgd.py
jsgd-61/python/jsgd_wrap.py
jsgd-61/python/jsgd_wrap.swg
jsgd-61/python/jsgd_wrap_wrap.c
jsgd-61/python/test_jsgd_train.py
jsgd-61/README
jsgd-61/ref/
jsgd-61/ref/generate_toy_data.m
jsgd-61/ref/plot_with_labels.m
jsgd-61/ref/read_svmlight.m
jsgd-61/ref/sgd_simple.m
jsgd-61/ref/sgd_simple_toy_data.m
jsgd-61/ref/write_svmlight.m
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