Text classifier. 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 s a python Open Source Toolkit for Chinese text categorization. The goal is to implement text categorization algorithm, so as to achieve the use in the generative 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
While providing rich functions, text-classifier internal modules adhere to low coupling, model adherence to inert loading, dictionary publication, and easy to use.
http://www.borntowin.cn/product/sentiment_classify
- text classifier
- modify config.py
- run segment.py -> train.py -> infer.py:
python train.py
python infer.py
- [done] LogisticRegression
- [done] Random Forest
- [done] Decision Tree
- [done] K-Nearest Neighbours
- [done] Naive bayes
- [done] Xgboost
- [done] Support Vector Machine(SVM)
- [done] MLP
- [done] Ensemble
- [done] Stack
- [done] CNN
- SentimentPolarityAnalysis
- Apache Licence 2.0