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1. sklearn Chinese text classification（Naive Bayes, Logistic Regression, XGboost, lightGBM, SVM, KNN,
Random Forest, Decision Tree, GBDT）to test the result of bio-text classification，the data i use（neg.txt, pos.txt）
The results are as follows：
| Naive Bayes |
0.9032786885245901 |
| Logistic Regression |
0.8737704918032787 |
| SVM |
0.8836065573770492 |
| Xgboost |
0.8442622950819673 |
| LightGBM |
0.8508196721311475 |
| knn |
0.6081967213114754 |
| RFC |
0.8721311475409836 |
| DT |
0.8 |
| GBDT |
0.8508196721311475 |
2. The method to optimize the above algorithm
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Use the classification method contained to test the result of classification
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