kernel_regularizer=regularizers.l2(0.001))正则化

model.add(Dense(25,activation='relu',kernel_regularizer=regularizers.l2(0.001)))#正则化 

#!/usr/bin/env python
# -*- coding:utf-8 -*- 
# Author: Jia ShiLin



'''
L1正则化
'''


import numpy as np
import pandas as pd
from matplotlib  import pyplot as plt

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

#data
data = pd.read_csv('hour.csv')

#特征工程
ohe_features = ['season','weathersit','mnth','hr','weekday']
for feature in ohe_features:
    dummies = pd.get_dummies(data[feature],prefix=feature,drop_first=False)
    data = pd.concat([data,dummies],axis=1)
    drop_features = ['instant','dteday','season','weathersit','weekday','atemp','mnth','workingday','hr','casual','registered']
    data = data.drop(drop