keras从入门到放弃(七）多层感知器训练

上篇讲了概念的东西

实战使用

泰坦尼克数据集，之前对它进行数据预处理

可以阅读上几篇

import pandas as pd
import keras
import numpy as np
data = pd.read_csv('./dataset/tt/train.csv')
y = data.Survived
x = data[['Pclass', 'Sex', 'Age', 'SibSp', 'Parch', 'Fare', 'Embarked']]
x.loc[:, 'Embarked_S'] = (x.Embarked == 'S').astype('int')
x.loc[:, 'Embarked_C'] = (x.Embarked == 'C').astype('int')
x.loc[:, 'Embarked_Q'] = (x.Embarked == 'Q').astype('int')
x.drop(['Embarked'],axis =1,inplace=True )
x.loc[:, 'Sex'] = (x.Sex == 'male').astype('int')
x.loc[:, 'Age'] = x.Age.fillna(x.Age.mean())
x.loc[:, 'p1'] = (x.Pclass == 1).astype('int')
x.loc[:, 'p2'] = (x.Pclass == 2).astype('
  

 

  
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文章来源: maoli.blog.csdn.net，作者：刘润森！，版权归原作者所有，如需转载，请联系作者。

原文链接：maoli.blog.csdn.net/article/details/88778417