Misclassification Rates for Four Methods of Group Classification: Impact of Predictor Distribution, Covariance Inequality, Effect Size, Sample Size, and Group Size Ratio  

Oleh:

Finch, W. Holmes ; Schneider, Mercedes K.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Educational and Psychological Measurement vol. 66 no. 02 (Apr. 2006), page 240-257.
Topik: discriminant analysis; regression trees; logistic regression; classification
Fulltext: 240.pdf (111.53KB)

Isi artikel

(PKPM) This study compares the classification accuracy of linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), logistic regression (LR), and classification and regression trees (CART) under a variety of data conditions. Past research has generally found comparable performance of LDA and LR, with relatively less research on QDA and virtually none onCART. This study uses Monte Carlo simulations to assess the crossvalidated predictive accuracy of these methods, while manipulating such factors as predictor distribution, sample size, covariance matrix inequality, group separation, and group size ratio. The results indicate thatQDAperforms as well as or better than the other alternatives in virtually all conditions. Suggestions for practitioners are provided.

Opini Anda

Klik untuk menuliskan opini Anda tentang koleksi ini!

Kembali