一个特别经典的建议大家试一下，concat_emb-> spartial dropout(0.2)->LSTM ->LSTM->concat(maxpool,meanpool)->FC。结合前面的任务难度定义，推荐的算法选型行为 Fasttext（垃圾邮件/主题分类） 特别简单的任务，要求速度TextCNN（主题分类/领域识别） 比较简单的任务，类别可能比较多，要求速度LSTM（情感分类/意...
(filters, kernel_size, padding='valid', activation='relu', strides=1)) model.add(MaxPooling1D(pool_size=pool_size)) # model.add(LSTM(lstm_output_size)) ## LSTM model.add(Bidirectional(LSTM(lstm_output_size))) ## Bi-LSTM model.add(Dense(6)) model.add(Activation('softmax')) model...
to(device) return input_batch, target_batch '''2.构建模型:LSTM(本实验结构图详见笔记)''' class TextLSTM(nn.Module): def __init__(self): super().__init__() # n_class是字母类别数(26),即嵌入向量维度 self.lstm = nn.LSTM(input_size=n_class, hidden_size=hidden_size) self.W = ...
(https://github.com/fate233/toutiao-multilevel-text-classfication-dataset)) -labels.csv -train.csv -valid.csv - embeddings - chinese_L-12_H-768_A-12/(取谷歌预训练好点的模型,已经压缩上传, keras-bert还可以加载百度版ernie(需转换,[https://github.com/ArthurRizar/tensorflow_ernie](https://...
(https://github.com/fate233/toutiao-multilevel-text-classfication-dataset)) -labels.csv -train.csv -valid.csv - embeddings - chinese_L-12_H-768_A-12/(取谷歌预训练好点的模型,已经压缩上传, keras-bert还可以加载百度版ernie(需转换,[https://github.com/ArthurRizar/tensorflow_ernie](https://...
The desired results will be obtained when the accuracy, F1 and recall value reach 1. On the contrary,when the values become 0, the worst result is obtained. For the multi-class classification problem,the precision and recall value of each class can be calculated separately, and then the perf...
详细代码和数据:https://github.com/huanghao128/zh-nlp-demo 数据预处理 这里使用的数据集只是用来演示文本分类任务,所以没有使用长篇的文章,而是使用的标题。原始数据集是在头条爬取的,在这里可以下载:https://github.com/fate233/toutiao-text-classfication-dataset ...
Let’s understand these concepts through the lens of an LSTM model. Training phase In the training phase, we will first set up the encoder and decoder. We will then train the model to predict the target sequence offset by one timestep. Let us see in detail on how to set up the encode...
一、智能文档处理介绍 智能文档处理（Intelligent Document Processing, IDP）是利用人工智能（AI）、机器学习（ML）、计算机视觉（CV）、自然语言处理（NLP）等技术自动化地捕获、理解、处理和分析文档内容的过程。不同于传统的文档管理系统，IDP能够处理结构化、半结构化和非结构化的文档，从而提取有用信息并将其转换...
NLP for classifying text. Using word Word2Vec word embedding and a neural net with bidirectional LSTM to categorize sentences provided by the user. - GitHub - chrislemke/nlp-text-classifier: NLP for classifying text. Using word Word2Vec word embedding a