Re: [問題] Homework 1

看板CS_SLT2005作者 (@_@"""")時間20年前 (2005/09/25 15:22), 編輯推噓0(000)
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※ 引述《hometoofar (家太遠了)》之銘言: : ※ 引述《rafan (@_@"""")》之銘言: : : Homework 1 is using k-nearest neighbor method, not SVM. : : Just forget it.The dataset is a multilabel one, i.e., : : one instance can have more than one target value (class : : labels). : : Since kNN is original designed for one target value, : : it is up to you that how to apply it on multilabel : : dataset. : Since we are using kNN here, does that mean we don't need to train it? We just : use the training data and kNN to predict what class label should a test entry : have and compare it to the true class label? Then we compare different values : of k and see which k would give the best result? I think you should use cross validation tecnique taught in class to decide k. After have a k, you use the whole training data to predict the testing data. -- ※ 發信站: 批踢踢實業坊(ptt.cc) ◆ From: 140.112.90.75
文章代碼(AID): #13Db1Bbf (CS_SLT2005)
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文章代碼(AID): #13Db1Bbf (CS_SLT2005)