人工智能,机器学习代码

上传者: bibibabibao | 上传时间: 2022-04-15 13:17:22 | 文件大小: 9.36MB | 文件类型: ZIP
人工智能,机器学习代码

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ML特征工程和优化方法","children":[{"title":"README.md <span style='color:#111;'> 37.53KB </span>","children":null,"spread":false}],"spread":true},{"title":"5.2 Markov","children":[{"title":"5.2 HMM.ipynb <span style='color:#111;'> 16.33KB </span>","children":null,"spread":false},{"title":"5.2 Markov.md <span style='color:#111;'> 21.75KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 21.75KB </span>","children":null,"spread":false}],"spread":true},{"title":"Liner Regression","children":[{"title":"1.Liner Regression.md <span style='color:#111;'> 7.40KB </span>","children":null,"spread":false},{"title":"demo","children":[{"title":"kc_test.txt <span style='color:#111;'> 178.18KB </span>","children":null,"spread":false},{"title":"housing_price.py <span style='color:#111;'> 1.76KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 6.80KB </span>","children":null,"spread":false},{"title":"kc_train.txt <span style='color:#111;'> 663.48KB </span>","children":null,"spread":false}],"spread":true},{"title":"README.md <span style='color:#111;'> 7.40KB </span>","children":null,"spread":false}],"spread":true},{"title":"3.1 Random Forest","children":[{"title":"3.1 Random Forest.md <span style='color:#111;'> 8.64KB </span>","children":null,"spread":false},{"title":"RandomForestRegression.ipynb <span style='color:#111;'> 48.89KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 8.64KB </span>","children":null,"spread":false}],"spread":true},{"title":"5.1 Bayes Network","children":[{"title":"5.1 Bayes Network.md <span style='color:#111;'> 18.82KB </span>","children":null,"spread":false},{"title":"Naive Bayes Classifier.ipynb <span style='color:#111;'> 4.64KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 18.82KB </span>","children":null,"spread":false}],"spread":true},{"title":"9. KNN","children":[{"title":"handwritingClass","children":[{"title":"handwritingClass.py <span style='color:#111;'> 10.79KB </span>","children":null,"spread":false},{"title":"trainingDigits.zip <span style='color:#111;'> 499.85KB </span>","children":null,"spread":false},{"title":"testDigits.zip <span style='color:#111;'> 236.21KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 4.77KB </span>","children":null,"spread":false}],"spread":true},{"title":"README.md <span style='color:#111;'> 25.70KB </span>","children":null,"spread":false}],"spread":true},{"title":"3.Desition Tree","children":[{"title":"Desition Tree.md <span style='color:#111;'> 12.29KB </span>","children":null,"spread":false},{"title":"DecisionTree.csv <span style='color:#111;'> 3.02MB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 12.29KB </span>","children":null,"spread":false},{"title":"DecisionTree.ipynb <span style='color:#111;'> 736.49KB </span>","children":null,"spread":false}],"spread":true},{"title":"2.Logistics Regression","children":[{"title":"2.Logistics Regression.md <span style='color:#111;'> 9.26KB </span>","children":null,"spread":false},{"title":"demo","children":[{"title":"CreditScoring.ipynb <span style='color:#111;'> 15.29KB </span>","children":null,"spread":false},{"title":"KaggleCredit2.csv.zip <span style='color:#111;'> 1.97MB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 224B </span>","children":null,"spread":false}],"spread":true},{"title":"README.md <span style='color:#111;'> 9.26KB </span>","children":null,"spread":false}],"spread":true},{"title":"3.3 XGBoost","children":[{"title":"3.3 XGBoost.md <span style='color:#111;'> 10.94KB </span>","children":null,"spread":false},{"title":"数据说明.txt <span style='color:#111;'> 357B </span>","children":null,"spread":false},{"title":"pima-indians-diabetes.csv <span style='color:#111;'> 23.48KB </span>","children":null,"spread":false},{"title":"3.3 XGBoost.ipynb <span style='color:#111;'> 1.90KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 10.94KB </span>","children":null,"spread":false}],"spread":true},{"title":"7. Clustering","children":[{"title":"corpus_train.txt <span style='color:#111;'> 229.76KB </span>","children":null,"spread":false},{"title":"K-Means.ipynb <span style='color:#111;'> 27.58KB </span>","children":null,"spread":false},{"title":"GMM.ipynb <span style='color:#111;'> 11.64KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 14.86KB </span>","children":null,"spread":false}],"spread":true},{"title":"5.3 Topic Model","children":[{"title":"HillaryEmail.ipynb <span style='color:#111;'> 16.69KB </span>","children":null,"spread":false},{"title":"HillaryEmails.csv <span style='color:#111;'> 24.43MB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 20.24KB </span>","children":null,"spread":false}],"spread":true},{"title":"4. SVM","children":[{"title":"news classification","children":[{"title":"svm_classification.ipynb <span style='color:#111;'> 17.10KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 2.83KB </span>","children":null,"spread":false}],"spread":true},{"title":"4. SVM.md <span style='color:#111;'> 18.21KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 18.21KB </span>","children":null,"spread":false}],"spread":true},{"title":"README.md <span style='color:#111;'> 3.66KB </span>","children":null,"spread":false},{"title":"3.2 GBDT","children":[{"title":"train_feat.txt <span style='color:#111;'> 445B </span>","children":null,"spread":false},{"title":"test_feat.txt <span style='color:#111;'> 445B </span>","children":null,"spread":false},{"title":"3.2 GBDT.md <span style='color:#111;'> 8.54KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 8.62KB </span>","children":null,"spread":false},{"title":"GBDT_demo.ipynb <span style='color:#111;'> 11.05KB </span>","children":null,"spread":false}],"spread":true},{"title":"6. EM","children":[{"title":"gmm_em","children":[{"title":"main.py <span style='color:#111;'> 1.24KB </span>","children":null,"spread":false},{"title":"gmm.py <span style='color:#111;'> 4.71KB </span>","children":null,"spread":false},{"title":"gmm.data <span style='color:#111;'> 5.31KB </span>","children":null,"spread":false},{"title":"sample.data <span style='color:#111;'> 4.90KB </span>","children":null,"spread":false},{"title":"genSample.py <span style='color:#111;'> 493B </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 747B </span>","children":null,"spread":false}],"spread":false},{"title":"README.md <span style='color:#111;'> 9.03KB </span>","children":null,"spread":false}],"spread":false},{"title":"3.4 LightGBM","children":[{"title":"3.4 LightGBM.ipynb <span style='color:#111;'> 4.36KB </span>","children":null,"spread":false},{"title":"3.4 LightGBM.md <span style='color:#111;'> 7.53KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 7.53KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]

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