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  • 2022-04-12 11:28
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KNN_CLASSIFICATION: 该项目使用K-最近邻居算法将数据分类为二进制标签。 数据说明包含在笔记本中 Support_Vector_Classification: 这是使用支持向量机对数据进行分类的分类项目。 数据说明包含在笔记本中 Titanic_Classification_Kaggle: 该项目使用KNN,决策树,随机森林和朴素贝叶斯等多种分类技术对乘客是否幸存进行分类。 效果最好的分类器用于预测结果。 数据描述包含在笔记本中。
Classification-master.zip
  • Classification-master
  • train.csv
    59.8KB
  • Titanic_Classification_Kaggle.ipynb
    302.8KB
  • KNN_Classification.ipynb
    94.4KB
  • Social_Network_Ads-Copy1.csv
    10.7KB
  • README.md
    682B
  • test.csv
    28KB
  • Support_Vector_Classification.ipynb
    5.2MB
内容介绍
KNN_CLASSIFICATION: This project deals with classifying the data into a binary label using the K-Nearest Neighbor algorithm. The data description is included in the noteboook Support_Vector_Classification: This is is classification project which uses Support Vector Machines to classify the data. Data description is included in the notebook Titanic_Classification_Kaggle: This project uses several classification techniques, namely, KNN, Decision Tree, Random Forest and Naive Bayes to classify whether the passenger survives or not. The best performing classifier is used to predict the result. Data description is included in the notebook.
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