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
