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文件名称:KNN
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- 上传时间：2013-05-11
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Implement the K nearest neighbor algorithm by your own instead of using available software.
2. Use K-fold cross validation to generate training and testing datasets. You should try different K values (3~8) to see how they affect your result.
3. Train the classifier using your training dataset, and test the classifier using your testing dataset.
4. Repeat the experiment (Step 2 and Step 3) 30 times. For each time, you need to record the training data accuracy and testing data accuracy. Finally, you can obtain the average training data accuracy and average testing data accuracy.
2. Use K-fold cross validation to generate training and testing datasets. You should try different K values (3~8) to see how they affect your result.
3. Train the classifier using your training dataset, and test the classifier using your testing dataset.
4. Repeat the experiment (Step 2 and Step 3) 30 times. For each time, you need to record the training data accuracy and testing data accuracy. Finally, you can obtain the average training data accuracy and average testing data accuracy.
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下载文件列表
KNN/Assignment 2 Classification.doc
KNN/KNN_1.m
KNN/KNN_2.m
KNN/Wine.csv
KNN
KNN/KNN_1.m
KNN/KNN_2.m
KNN/Wine.csv
KNN
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