chapter4linearmodelsforclassification(參考版)
2025-07-18 18:04本頁面
【正文】 s Perceptron Learning Algorithm ? Convergence If the classes are linearly separable, the algorithm converges to a separating hyperplane in a finite number of steps. ? Problems Optimal Separating Hyperplanes ? Optimal separating hyperplane maximize the distance to the closest point from either class By doing some calculation, the criterion can be rewritten as Optimal Separating Hyperplanes ? The Lagrange function ? KarushKuhnTucker (KKT)conditions ? 怎么解？ Optimal Separating Hyperplanes ? Support points 由此可得 事實(shí)上，參數(shù)估計(jì)值只由幾個(gè)支撐點(diǎn)決定 Optimal Separating Hyperplanes ? Some discussion Separating Hyperplane vs LDA Separating Hyperplane vs Logistic Regression When the data are not separable, there will be no feasible solution to this problem?SVM 謝謝大家 ! 。Chapter 4 Linear Models for Classification ? Introduction ? Linear Regression ? Linear Discriminant Analysis ? Logistic Regression ? Separating Hyperplanes Introduction ? The discriminant function for the kth indicator respon
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