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| author | Joe Zhao <ztuowen@gmail.com> | 2015-04-11 17:46:19 +0800 |
|---|---|---|
| committer | Joe Zhao <ztuowen@gmail.com> | 2015-04-11 17:46:19 +0800 |
| commit | 85a4962556b67d1cc0668ecb2fbb03b3b4dd6e7e (patch) | |
| tree | 3059605ab0707b5530330dacdd9445b59bd73669 /model/ranksvm.h | |
| parent | 5d57accc3e1bc2b89c1e7753f7dbb40f3c8f575a (diff) | |
| download | ranksvm-85a4962556b67d1cc0668ecb2fbb03b3b4dd6e7e.tar.gz ranksvm-85a4962556b67d1cc0668ecb2fbb03b3b4dd6e7e.tar.bz2 ranksvm-85a4962556b67d1cc0668ecb2fbb03b3b4dd6e7e.zip | |
completed & tested, train & predict
Diffstat (limited to 'model/ranksvm.h')
| -rw-r--r-- | model/ranksvm.h | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/model/ranksvm.h b/model/ranksvm.h index e82b6be..aa5e1ca 100644 --- a/model/ranksvm.h +++ b/model/ranksvm.h @@ -26,7 +26,7 @@ protected: int fsize; public: virtual int train(DataList &D)=0; - virtual int predict(DataList &D,std::list<double> &res)=0; + virtual int predict(DataList &D,std::vector<double> &res)=0; // TODO Not sure how to construct this // Possible solution: generate a nxn matrix each row contains the sorted list of ranker result. int saveModel(const std::string fname); |