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שיטת השכנים הקרובים ביותר (K-Nearest Neighbors)×ניתוח שונות רב-משתני (MANOVA)×
תחוםלמידת מכונהסטטיסטיקה
משפחהMachine learningHypothesis test
שנת המקור19671932
הוגה השיטהCover, T.M. & Hart, P.E.Samuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.)
סוגInstance-based (non-parametric) learningParametric multivariate mean comparison
מקור מכונןCover, T.M. & Hart, P.E. (1967). Nearest Neighbor Pattern Classification. IEEE Transactions on Information Theory, 13(1), 21–27. DOI ↗Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574
כינוייםKNN, K-En Yakın Komşu (KNN), nearest neighbor classifier, instance-based learningMultivariate ANOVA, Çok Değişkenli ANOVA (MANOVA)
קשורות55
תקצירK-Nearest Neighbors (KNN), formalized by Cover and Hart in 1967, is a non-parametric, instance-based method that classifies or predicts a new observation by looking at the k closest examples in the training data. For classification it takes a majority vote among those neighbors; for regression it averages their values.MANOVA is a parametric hypothesis test that simultaneously compares group means across multiple continuous dependent variables, controlling the inflation of Type I error that would result from running separate ANOVAs. Key multivariate test statistics — Wilks' Lambda, Pillai's Trace, Hotelling-Lawley Trace, and Roy's Greatest Root — were developed between the 1930s and 1950s, with Wilks' Lambda formalised by Samuel Stanley Wilks in 1932.
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ScholarGateהשוואת שיטות: K-Nearest Neighbors · MANOVA. אוחזר בתאריך 2026-06-18 מתוך https://scholargate.app/he/compare