本程序使用路透社数据集，简单、广泛使用的文本分类数据集
# coding=utf-8 importnumpyasnpfromkeras.datasetsimportreutersfromkerasimportmodelsfromkerasimportlayersfrommmatplotlibimpoporas min_log_level']='2'#数据量化到def vectorize _ sequences (sequences，dimension=) dimension () for i，sequenceinceinsion sequence ]=1返回结果# one-hot代码defto_one dimension=46 ) : results=NP.zeros ((len (标签)，dimension labelinenumerate labels ) 3360 results label ]=1returnresultsdefmulticlassclassification (: )数据集(train_data，) test _ labels (=Reuters.load _ data (num _ words=10000 ) x_train=vectorize_sequences ) train_data ) x_ y _ train=to _ one _ hot (train _ labels ) y_test=to_one_hot )构建网络model=models.sequenttts activation='relu ' ) ) model.add ) layers.dense ) ) ) 652 activation='softmax ' ) #型号model.com pipe 编译loss='categorical_crossentropy '，测量结果=[ ' accuracy ' ]训练模型x _ val=x _ train [ :1000 ] partity y _ val partial_y_train=y _ train [ 10003360 ] history=model.fit (partial _ x _ train，partial _ y _ train y _ test (打印) results ) history _ dict=history.history ACC=history _ dict [ ' accuracy ' ] val _ ACC=history， label='Training acc ' )，蓝色实线PLT.plot ) epochs，val_acc，' label=' validation ACC ' (PLT.title (traitle ) )