Metadata-Version: 2.1
Name: pytextclassifier
Version: 0.0.1
Summary: Text Classifier, Text Classification
Home-page: https://github.com/shibing624/pytextclassifier
Author: XuMing
Author-email: xuming624@qq.com
License: Apache 2.0
Description: ![alt text](docs/logo.svg)
        
        
        [![License Apache 2.0](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](./LICENSE) ![](https://img.shields.io/badge/Language-Python-blue.svg) ![](https://img.shields.io/badge/Python-3.X-red.svg) ![](https://img.shields.io/badge/Python-2.X-red.svg)
        
        # text-classifier
        Text classifier and cluster. It can be applied to the fields of sentiment polarity analysis, text risk classification and so on, and it supports multiple classification algorithms.
        
        -----
        
        
        **text-classifier** is a python Open Source Toolkit for text classification and text clustering. The goal is to implement text analysis algorithm, so as to achieve the use in the production environment. **text-classifier** has the characteristics of clear algorithm, high performance and customizable corpus.
        
        **text-classifier** provides the following functions：
        > * Classifier
          * LogisticRegression
          * MultinomialNB
          * KNN
          * SVM
          * RandomForest
          * DecisionTreeClassifier
          * Xgboost
          * Neural Network
        > * Evaluate
          * Precision
          * Recall
          * F1
        > * Test
          * Chi-square test
        > * Cluster
          * MiniBatchKmeans
        
        While providing rich functions, **text-classifier** internal modules adhere to low coupling, model adherence to inert loading, dictionary publication, and easy to use.
        
        ------
        ## demo 
        
        https://www.borntowin.cn/product/sentiment_classify
        
        ------
        
        ## Usage
        ### Requirements and Installation
        ```
        git clone https://github.com/shibing624/text-classifier.git
        pip3 install -r requirements.txt
        ```
        
        ### Example Usage
        
        1. Preprocess with segment
        ```
        python3 preprocess.py
        ```
        
        2. Train model
        
        you can change model with edit `config.py` and train model.
        ```
        python3 train.py
        ```
        
        3. Predict with test data
        ```
        python3 infer.py
        ```
        
        
        ## Algorithm
          - [x] LogisticRegression
          - [x] Random Forest
          - [x] Decision Tree
          - [x] K-Nearest Neighbours
          - [x] Naive bayes
          - [x] Xgboost
          - [x] Support Vector Machine(SVM)
          - [x] MLP
          - [x] Ensemble
          - [x] Stack
          - [x] Xgboost_lr
          - [x] text CNN
          - [x] text RNN
          - [x] fasttext
          - [x] HAN
          - [x] Kmenas
        
        
        ## Thanks
          - SentimentPolarityAnalysis
        
        ## Licence
          - Apache Licence 2.0
        
Keywords: pytextclassifier,textclassifier,classifier,textclassification
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: Natural Language :: Chinese (Simplified)
Classifier: Natural Language :: Chinese (Traditional)
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Text Processing
Classifier: Topic :: Text Processing :: Indexing
Classifier: Topic :: Text Processing :: Linguistic
Description-Content-Type: text/markdown
