kaggle入门篇一【手写数字识别】

来源：互联网发布：cpu百分率 linux命令编辑：程序博客网时间：2024/06/05 02:16

作为入门，

我使用了keras

代码：借鉴了很多别人的方法。

# -*- coding: utf-8 -*-"""Created on Fri Apr 21 11:10:17 2017@author: Administrator"""from keras.utils import np_utilsfrom keras.models import Sequentialfrom keras.layers import Dropout,Dense,Activation,Convolution2D, MaxPooling2D, Flattenimport numpy as npimport pandas as pdtest=pd.read_csv(r"F:\kaggle_file\shouxieshuzi\test.csv")test=np.array(test)data=pd.read_csv(r"F:\kaggle_file\shouxieshuzi\train.csv")train_Labels=data['label']del(data['label'])train_Data=data/255train_Labels = np_utils.to_categorical(train_Labels, num_classes=10)data=np.array(train_Data)train_Data=np.array(train_Data).reshape(42000,1,28,28)test=test.reshape(28000,1,28,28)###预处理def Cmodel():      #create model      model = Sequential()      model.add(Convolution2D(nb_filter=32,nb_row=5,nb_col=5,border_mode='same',dim_ordering='th',input_shape=(1,28,28),activation='relu'))      model.add(MaxPooling2D(pool_size=(2,2),strides=(2, 2),border_mode='same'))          model.add(Convolution2D(64,5,5,activation='relu'))      model.add(MaxPooling2D(pool_size=(2,2),border_mode='same'))      model.add(Dropout(0.2))          model.add(Flatten())      model.add(Dense(1024,activation='relu'))          model.add(Dense(50,activation='relu'))          model.add(Dense(10,activation='softmax'))      #Compile model      model.compile(loss='categorical_crossentropy',optimizer='adam',metrics=['accuracy'])      return model     model = Cmodel()  model.fit(train_Data,train_Labels,nb_epoch=10,batch_size=100) ######新模型predict=model.predict(test)predict=predict.argmax(1)predict=pd.DataFrame(predict)predict.to_csv('result.csv')

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