def mobilesoft_cart(fileNameParam, fileToWriteP):
testAndTrainData = IO_.giveTestAndTrainingData(fileNameParam)
trainData = testAndTrainData[0]
testData = testAndTrainData[1]
selected_training_data = pca_mobilesoft.getPCAedFeatures(trainData)
print "Size of selected training data : ", np.shape(selected_training_data)
print "=" * 50
dict_of_results = param_exp_classifier.runCART(selected_training_data,
testData, 0.90)
reportStr = param_exp_analysis.analyzeThis(dict_of_results)
IO_.writeStrToFile(fileToWriteP, reportStr)
def speedup_random_forest(fileNameParam, fileToWriteP): testAndTrainData = IO_.giveTestAndTrainingData(fileNameParam) trainData = testAndTrainData[0] testData = testAndTrainData[1] #print trainData selected_training_data = pca_mobilesoft.getPCAedFeatures(trainData) print "Size of selected training data : ", np.shape(selected_training_data) print "="*50 dict_of_results = runRandomForest(selected_training_data, testData) reportStr = param_exp_analysis.analyzeThis(dict_of_results) IO_.writeStrToFile(fileToWriteP, reportStr)
def mobilesoft_cart(fileNameParam, fileToWriteP): indexVector = [0, 5, 10, 12, 13, 18, 19, 20] testAndTrainData = IO_.giveTestAndTrainingData(fileNameParam) trainData = testAndTrainData[0] testData = testAndTrainData[1] selected_training_data = createMobileSoftFeatures(trainData, indexVector) print "Size of selected training data : ", np.shape(selected_training_data) print "="*50 print "Glimpse at selected features (10th entry): \n", selected_training_data.iloc[9, :] print "="*50 print "Glimpse at labels (10th entry): \n", testData.iloc[9] print "="*50 dict_of_results = param_exp_classifier.runCART(selected_training_data, testData, 0.90) reportStr = param_exp_analysis.analyzeThis(dict_of_results) IO_.writeStrToFile(fileToWriteP, reportStr)
def experiemnt_random_forest(fileNameParam, fileToWriteP):
testAndTrainData = IO_.giveTestAndTrainingData(fileNameParam)
print "This is 'experiemnt_random_forest' "
# settign up train data
trainData = testAndTrainData[0]
original_rows = trainData.shape[0]
original_cols = trainData.shape[1]
print "Size of training data : rows: {}, columns: {}".format( original_rows , original_cols )
# settign up test data
testData = testAndTrainData[1]
dict_of_results = param_exp_classifier.runRandomForest(trainData, testData)
reportStr = param_exp_analysis.analyzeThis(dict_of_results)
IO_.writeStrToFile(fileToWriteP, reportStr)
def experiemnt_random_forest(fileNameParam, fileToWriteP):
testAndTrainData = IO_.giveTestAndTrainingData(fileNameParam)
print "This is 'experiemnt_random_forest' "
# settign up train data
trainData = testAndTrainData[0]
original_rows = trainData.shape[0]
original_cols = trainData.shape[1]
print "Size of training data : rows: {}, columns: {}".format(
original_rows, original_cols)
# settign up test data
testData = testAndTrainData[1]
dict_of_results = param_exp_classifier.runRandomForest(trainData, testData)
reportStr = param_exp_analysis.analyzeThis(dict_of_results)
IO_.writeStrToFile(fileToWriteP, reportStr)