Running models

python run.py [TRAIN_PATH] [TEST_PATH] [RESULT_PATH] [MODEL] [HYPER PARAMETERS]

MODELS = [ UserCf, ItemCf, MF, MFImp, MFGLab, MFContentGLab, UserCfGLab, ItemCfGLab, UserCfContentGLab, ItemCfContentGLab, TextSimilarity, TagRule, ]

HYPER_PARAMTERS are specific to a model lambda, distance, UB (etc)

example: python run.py data/train.csv data/validate.csv data/validate.csv.results.mf1 MF "[11, 0.1, 0]"

Ensemble

python dtree.py [TRAIN_SET] [TEST_SET] [TRAIN] [TEST] [RESULT_PATH]

Name		Name	Last commit message	Last commit date
Latest commit History 65 Commits
data		data
kfold		kfold
libpmf		libpmf
recommenders		recommenders
util		util
validate		validate
.gitignore		.gitignore
README.md		README.md
SVM_UB.py		SVM_UB.py
cmd		cmd
compare.py		compare.py
contrast.py		contrast.py
dtree.py		dtree.py
expand.py		expand.py
feature_reduction.py		feature_reduction.py
kfold-output		kfold-output
kfold.py		kfold.py
kmeans.py		kmeans.py
logistic-regression.ipynb		logistic-regression.ipynb
lreg.py		lreg.py
patterns.r		patterns.r
pre-process.ipynb		pre-process.ipynb
run.py		run.py
run.sh		run.sh
scrap.ipynb		scrap.ipynb
validate.sh		validate.sh