python_data_analysis_and_mining_action-master-6

#-*- coding: utf-8 -*-
# pylint: disable=E1101
from random import shuffle
 
import matplotlib.pyplot as plt
import pandas as pd
from keras.layers.core import Activation, Dense
from keras.models import Sequential
from scipy.interpolate import lagrange
from sklearn.externals import joblib
from sklearn.metrics import confusion_matrix, roc_curve
from sklearn.tree import DecisionTreeClassifier
"""
cm_plot-->自定义混淆矩阵可视化
programmer_1-->使用拉格朗日插值法进行插值
programmer_2-->构建CART决策树模型，进行预测给出训练结果，并且绘制ROC曲线
programmer_3-->使用神经网络模型，进行预测给出训练结果，并且绘制ROC曲线
"""
 
 
def cm_plot(y, yp):
    cm = confusion_matrix(y, yp)
 
    plt.matshow(cm, cmap=plt.cm.Greens)
    plt.colorbar()
 
    for x in range(len(cm)):
        for y in range(len(cm)):
            plt.annotate(
                cm[x, y],
                xy=(x, y),
                horizontalalignment='center',
                verticalalig