import pandas as pd import ROC_Curve from sklearn.cross_validation import train_test_split # regr=linear_model.LogisticRegression() data=pd.read_csv(open('/users/biprade/downloads/Project/train_Complete.csv')) target=data['TripType'] del data['TripType'] X, y =data,target X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=.25, random_state=42) a= ROC_Curve.getROCScore(X_train,y_train,X_test,y_test,'LogisticRegression',Cvalue=1000) print a[0],a[1]
import pandas as pd import ROC_Curve from sklearn.cross_validation import train_test_split data=pd.read_csv(open('train_Complete.csv')) target=data['TripType'] del data['TripType'] X, y =data,target X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=.25, random_state=42) a= ROC_Curve.getROCScore(X_train,y_train,X_test,y_test,'DecisionTree') print a[0],a[1]
import pandas as pd from sklearn.metrics import accuracy_score from sklearn import linear_model from sklearn import tree from sklearn.multiclass import OneVsRestClassifier from sklearn.svm import LinearSVC from sklearn.ensemble import BaggingClassifier from sklearn.feature_selection import chi2 from sklearn.feature_selection import SelectKBest from sklearn.cross_validation import train_test_split import ROC_Curve data = pd.read_csv(open("train_Complete.csv")) target = data["TripType"] del data["TripType"] X, y = data, target X_features = 150 ch2 = SelectKBest(chi2, k=X_features) X = ch2.fit_transform(X, y) X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42) a = ROC_Curve.getROCScore(X_train, y_train, X_test, y_test, "Bagging") print a[0], a[1]
from sklearn.metrics import confusion_matrix from sklearn.multiclass import OneVsRestClassifier from sklearn.svm import LinearSVC import pandas as pd from sklearn.metrics import log_loss import numpy as np import ROC_Curve from sklearn.externals import joblib from sklearn.metrics import accuracy_score from sklearn.cross_validation import train_test_split from sklearn.feature_selection import chi2 from sklearn.feature_selection import SelectKBest from sklearn.preprocessing import label_binarize from sklearn.cross_validation import train_test_split data=pd.read_csv(open('/users/biprade/downloads/Project/train_Complete.csv')) target=data['TripType'] del data['TripType'] X, y =data,target X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=.25, random_state=42) a= ROC_Curve.getROCScore(X_train,y_train,X_test,y_test,'LinearSVC',Cvalue=1) print a[0],a[1]
import pandas as pd import ROC_Curve from sklearn.cross_validation import train_test_split from sklearn.multiclass import OneVsRestClassifier data=pd.read_csv(open('/users/biprade/downloads/Project/train_Complete.csv')) target=data['TripType'] del data['TripType'] X, y =data,target X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=.25, random_state=42) a= a= ROC_Curve.getROCScore(X_train,y_train,X_test,y_test,'NaiveBayes',alphaValue=0.6) print a[0],a[1]