ANN 入门 ，简单的神经系统网络

数据的链接是Kaggle 关于人心脏病的参数的
https://www.kaggle.com/ronitf/heart-disease-uci

先读取数据

import pandas as pd
import numpy as np
dataset=pd.read_csv
dataset.head(10)("heart.csv")在这里插入代码片`

经过数据介绍发现 虽然都是数据信息可是其中有四栏是分类数据，必须进行dummy 的处理

dataset=pd.get_dummies(dataset,columns=['sex','fbs','exang','thal'])
X=dataset.iloc[:,:-1].values
y=dataset.iloc[:,-1].values

进行数据进行处理

from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler

sc=StandardScaler()
X_train=sc.fit_transform(X_train)
X_test=sc.transform(X_test)

用keras构建简单的神经系统网络并进行机器学期

from keras.models import Sequential
from keras.layers import Dense,Dropout

classifier=Sequential()
classifier.add(Dense(11,activation='relu'))
classifier.add(Dropout(0.2))
classifier.add(Dense(1,activation='sigmoid'))
classifier.compile(optimizer='Adam',loss='binary_crossentropy',metrics=['accuracy'])
classifier.fit(X_train,y_train,validation_data=(X_test,y_test),epochs=1000)

结果非常完美

再用代码算一遍score

y_pred=classifier.predict_classes(X_test)
from matplotlib import  pyplot as plt
from sklearn.metrics import confusion_matrix,accuracy_score

accuracy_score(y_pred,y_test)