def performLogiRegression(fileNamaParam): # get test and train data together test_trainData = utility.giveMePandaDataFrame(fileNamaParam) #print test_trainData.head() # get tarining data trainingCols = test_trainData.columns[0:21] trainData = test_trainData[trainingCols] #print "<----------Training data matrix---------->" #print trainData.head() ############### #print trainData.describe() testColn = test_trainData.columns[-1] testData = test_trainData[testColn] #print "<----------Test data column---------->" #print testData.head() #test_trainData['intercept'] = 1.0 ################# print "<------------ Performing Logistic Regression ------------->" logisticRModel = linear_model.LogisticRegression(C=1e5, penalty='l1') ### if you dont fit , you will get an error logisticRModel.fit(trainData, testData) ##print "Output of score (mean accuracy of test features and prediction classs) " ##print logisticRModel.score(trainData, testData) print "Output of co-efficients ={}".format(logisticRModel.coef_) print "Output of intercept ={}, n_iter_ = {} ".format( logisticRModel.intercept_, logisticRModel.n_iter_)
def performLogiRegression(fileNamaParam): # get test and train data together test_trainData = utility.giveMePandaDataFrame(fileNamaParam) #print test_trainData.head() # get tarining data trainingCols = test_trainData.columns[0:21] trainData = test_trainData[trainingCols] #print "<----------Training data matrix---------->" #print trainData.head() ############### #print trainData.describe() testColn = test_trainData.columns[-1] testData = test_trainData[testColn] #print "<----------Test data column---------->" #print testData.head() #test_trainData['intercept'] = 1.0 ################# print "<------------ Performing Logistic Regression ------------->" logisticRModel = linear_model.LogisticRegression(C=1e5, penalty='l1') ### if you dont fit , you will get an error logisticRModel.fit(trainData, testData) print "Output of score (mean accuracy of test features and prediction classs) " print logisticRModel.score(trainData, testData) print "Output of co-efficients ={}".format(logisticRModel.coef_) print "Output of intercept ={}, n_iter_ = {} ".format(logisticRModel.intercept_, logisticRModel.n_iter_)
def giveTestAndTrainingData(fileNamaParam): import utility # get test and train data together test_trainData = utility.giveMePandaDataFrame(fileNamaParam) # training data trainingCols = test_trainData.columns[0:21] trainData = test_trainData[trainingCols] # test data testColn = test_trainData.columns[-1] testData = test_trainData[testColn] return trainData, testData