def randomforest_test(filenames):
for filename in filenames:
rmse_series_randomforest=[]
covariance_series_randomforest=[]
for k in range (1,101):
randomforestlearner = Randomforestlearner(k=k)
get_set = randomforestlearner.getflatcsv(filename)
get_set_60pr,get_set_40pr = numpy.split(get_set,[600])
(X,Y) = numpy.split(get_set,[2],axis=1)
(XTrain,XTest) = numpy.split(X,[600])
(Ytrain,YTest) = numpy.split(Y,[600])
Y_Test = np.squeeze(np.asarray(YTest))
randomforestlearner.addEvidence(XTrain,Ytrain)
Y_Return = numpy.array(randomforestlearner.query(XTest))
rmse_series_randomforest.append(get_rmse(Y_Test,Y_Return))
covariance_series_randomforest.append(get_correlation(Y_Test,Y_Return))
return (rmse_series_randomforest,covariance_series_randomforest)
