1、加載IMDB數(shù)據(jù)集

# -*- coding: utf-8 -*- """ Created on Wed May 22 13:12:05 2019@author: liuxing @email:lx@lxaipro.com """ from keras.datasets import imdb #每個(gè)樣本特征為最多的10000個(gè)單詞，每個(gè)樣本每個(gè)單詞被賦予了一個(gè)ID即索引 (trainData,trainLabels),(testData,testLabels)=imdb.load_data(num_words=10000)print(trainData[0]) print(trainLabels[0])

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4, 226, 22, 21, 134, 476, 26, 480, 5, 144, 30, 5535, 18, 51, 36, 28, 224, 92, 25, 104, 4, 226, 65, 16, 38, 1334, 88, 12, 16, 283, 5, 16, 4472, 113, 103, 32, 15, 16, 5345, 19, 178, 32]
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解碼單詞索引，查看評(píng)論原文

# -*- coding: utf-8 -*- """ Created on Wed May 22 13:12:05 2019@author: liuxing @email:lx@lxaipro.com """ from keras.datasets import imdb #每個(gè)樣本特征為最多的10000個(gè)單詞，每個(gè)樣本每個(gè)單詞被賦予了一個(gè)ID即索引 (trainData,trainLabels),(testData,testLabels)=imdb.load_data(num_words=10000)print(trainData[0]) print(trainLabels[0]) wordIndex=imdb.get_word_index() i=0 for (key,value) in wordIndex.items():print("|{}=>{}|".format(key,value),end='')i+=1;if i>5:breakindexWord=dict([(value,key) for (key,value) in wordIndex.items()]) trainWords=' '.join([indexWord.get(i-3,'?') for i in trainData[0]]) print(trainWords)

運(yùn)行結(jié)果如下：

[1, 14, 22, 16, 43, 530, 973, 1622, 1385, 65, 458, 4468, 66, 3941, 4, 173, 36, 256, 5, 25, 100, 43, 838, 112, 50, 670, 2, 9, 35, 480, 284, 5, 150, 4, 172, 112, 167, 2, 336, 385, 39, 4, 172, 4536, 1111, 17, 546, 38, 13, 447, 4, 192, 50, 16, 6, 147, 2025, 19, 14, 22, 4, 1920, 4613, 469, 4, 22, 71, 87, 12, 16, 43, 530, 38, 76, 15, 13, 1247, 4, 22, 17, 515, 17, 12, 16, 626, 18, 2, 5, 62, 386, 12, 8, 316, 8, 106, 5, 4, 2223, 5244, 16, 480, 66, 3785, 33, 4, 130, 12, 16, 38, 619, 5, 25, 124, 51, 36, 135, 48, 25, 1415, 33, 6, 22, 12, 215, 28, 77, 52, 5, 14, 407, 16, 82, 2, 8, 4, 107, 117, 5952, 15, 256, 4, 2, 7, 3766, 5, 723, 36, 71, 43, 530, 476, 26, 400, 317, 46, 7, 4, 2, 1029, 13, 104, 88, 4, 381, 15, 297, 98, 32, 2071, 56, 26, 141, 6, 194, 7486, 18, 4, 226, 22, 21, 134, 476, 26, 480, 5, 144, 30, 5535, 18, 51, 36, 28, 224, 92, 25, 104, 4, 226, 65, 16, 38, 1334, 88, 12, 16, 283, 5, 16, 4472, 113, 103, 32, 15, 16, 5345, 19, 178, 32] 1 |fawn=>34701||tsukino=>52006||nunnery=>52007||sonja=>16816||vani=>63951||woods=>1408|? this film was just brilliant casting location scenery story direction everyone's really suited the part they played and you could just imagine being there robert ? is an amazing actor and now the same being director ? father came from the same scottish island as myself so i loved the fact there was a real connection with this film the witty remarks throughout the film were great it was just brilliant so much that i bought the film as soon as it was released for ? and would recommend it to everyone to watch and the fly fishing was amazing really cried at the end it was so sad and you know what they say if you cry at a film it must have been good and this definitely was also ? to the two little boy's that played the ? of norman and paul they were just brilliant children are often left out of the ? list i think because the stars that play them all grown up are such a big profile for the whole film but these children are amazing and should be praised for what they have done don't you think the whole story was so lovely because it was true and was someone's life after all that was shared with us all

總結(jié)

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