method = "SuperGrep"
print method
shutil.rmtree("cleanData/", True)
grep = Grep(True)
grep.initalPreprocess(DR, DT, L, TEST)
grep.testDirToOutput("cleanData/TEST/", "cleanData/" )
with open("cleanData/output.txt") as methodOutput:
for line in methodOutput.read().split():
finalOutput.write(method + "," + line + "\n")
method = "MultivariantBayes"
print method
shutil.rmtree("cleanData/", True)
bayes = Bayes('multivariant')
bayes.initalPreprocess(DR, DT, L, TEST, "custom", 1, False)
validate = CrossValidate("cleanData")
featureSelector = MIFeatureSelector()
validate.regularBayes(bayes, featureSelector, DISPLAY_ACCURACY)
with open("cleanData/output.txt") as methodOutput:
for line in methodOutput.read().split():
finalOutput.write(method + "," + line + "\n")
method = "MultinomialBayes"
print method
shutil.rmtree("cleanData/", True)
bayes = Bayes('multinomial')
bayes.initalPreprocess(DR, DT, L, TEST, "custom", 1, False)
validate = CrossValidate("cleanData")
featureSelector = FeatureSelector() # Multinomial does much worse with MIFeatureSelector()
validate.regularBayes(bayes, featureSelector, DISPLAY_ACCURACY)
