GitHub - frankpengyuan/course

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
azure		azure
clean		clean
fea		fea
localtest		localtest
raw		raw
rocfigures		rocfigures
sub		sub
.gitattributes		.gitattributes
README.txt		README.txt
clean.py		clean.py
cmap		cmap
extfea1.py		extfea1.py
extfea1_csv.py		extfea1_csv.py
extfea2.py		extfea2.py
extfea2_csv.py		extfea2_csv.py
model_complex_t.py		model_complex_t.py
omap		omap
sample.py		sample.py
stdmodel_adaboost_o.py		stdmodel_adaboost_o.py
stdmodel_adaboost_t.py		stdmodel_adaboost_t.py
stdmodel_csvm_o.py		stdmodel_csvm_o.py
stdmodel_csvm_t.py		stdmodel_csvm_t.py
stdmodel_extratrees_o.py		stdmodel_extratrees_o.py
stdmodel_extratrees_t.py		stdmodel_extratrees_t.py
stdmodel_randomforest_PCA_t.py		stdmodel_randomforest_PCA_t.py
stdmodel_randomforest_o.py		stdmodel_randomforest_o.py
stdmodel_randomforest_t.py		stdmodel_randomforest_t.py
umap		umap

Repository files navigation

prerequests: 
python evrionment
python package: numpy, sklearn

put the raw data into ./raw
clean.py will clean the data
extfea1 / 2 will extract feature from the cleaned data
sample.py is for split the data into two parts for local test
all stdmodel_*.py are the modelling scripts, since I included the uamp file here, thus you can run them even without raw data