Logistic 多分类

#!/usr/bin/env python3# -*- coding: utf-8 -*-"""Created on Wed Dec 20 14:54:31 2017@author: wayne"""import pandas as pdimport numpy as npfrom sklearn import preprocessingfrom sklearn.linear_model import LogisticRegressiondf = pd.read_excel("data.xlsx")df = df.dropna()cat_vars = ['relationship', 'class', 'scenario', 'object']target = 'violence'Y = df[target]for var in cat_vars:    cat_list = pd.get_dummies(df[var], prefix=var)    df = df.join(cat_list)delete_vars = cat_vars + list(target)df_vars = df.columns.values.tolist()to_keep = [i for i in df_vars if i not in delete_vars]X = df[to_keep]min_max_scaler = preprocessing.MinMaxScaler(feature_range=(0,1))X_scale = min_max_scaler.fit_transform(X)clf = LogisticRegression()clf.fit(X_scale, Y)coefficients = pd.DataFrame({"Feature":X.columns,"Coefficients0":np.transpose(clf.coef_[0,:])\                             ,"Coefficients1":np.transpose(clf.coef_[1,:])\                             ,"Coefficients2":np.transpose(clf.coef_[2,:])})intercepts = clf.intercept_    predicted = clf.predict(X_scale)accuracy_train = (predicted == Y).mean()print(accuracy_train)