帮助我理解记忆---**Slide Content Extraction:** **Title/Header:** 2.1 文本分类概述 (Text Classification Overview) **Sub-header:** 文本分类的一般步骤: (General Steps of Text Classification:) **Steps:** ① 定义阶段: 定义数据以及分类体系, 具体分为哪些类别, 需要哪些数据。 (Definition Phase: Define the data and classification system, specifically which categories it is divided into, and what data is needed.) ② 数据预处理: 对文档做分词、去停用词等准备工作。 (Data Preprocessing: Perform preparation work such as word segmentation and stop word removal on documents.) ③ 数据特征提取: 对文档矩阵进行降维, 提取训练集中最有用的特征。(文本向量化表示) (Data Feature Extraction: Reduce the dimensionality of the document matrix and extract the most useful features from the training set. (Text vectorization representation)) ④ 模型训练阶段: 选择具体的分类模型以及算法, 训练出文本分类器。 (Model Training Phase: Select specific classification models and algorithms, and train the text classifier.) ⑤ 评测阶段: 在测试集上测试并评价分类器的性能。 (Evaluation Phase: Test and evaluate the performance of the classifier on the test set.) ⑥ 应用阶段: 应用性能最高的分类模型对待分类文档进行分类。 (Application Phase: Apply the classification model with the highest performance to classify documents to be classified.)