By Ludmila I. Kuncheva
This identify covers numerous predictive version mixture equipment, for either express and numeric aim variables (bagging, boosting, etc.). It makes use of particular situations to demonstrate specific issues and makes connection with present literature (many references are from the early 2000s). a few MATLAB resource code is equipped, yet no longer on a laptop readable medium.
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Additional info for Combining Pattern Classifiers: Methods and Algorithms
The most natural way for that is to calculate the weighted m^ i and S^ i . Let W( j) be the weight of zj [ Z, W i Pobject c i be the sum of the weights of all objects in Z from vi , and W ¼ i¼1 W be the total sum of weights for Z. Then m^ i(w) ¼ 1 X W( j)zj W i l(z )¼v j (2:12) i and 1 X S^ (w) ¼ i W( j)(zj À m^ i )(zj À m^ i )T i W l(z )¼v j (2:13) i 5 We use the maximum likelihood estimate of the covariance matrices and note that this estimate is biased. P For an unbiased estimate take S^ i ¼ 1=(Ni À 1) l(zj )¼vi (zj À m^ i )(zj À m^ i )T .
Therefore, using the true posterior probabilities or an equivalent set of discriminant functions guarantees the smallest possible error rate, called the Bayes error. Since the true probabilities are never available in practice, it is impossible to calculate the exact Bayes error or design the perfect Bayes classifier. Even if the probabilities were given, it will be difficult to find the classification regions in Rn and calculate the integrals. 3. 6 Multinomial Selection Procedure for Comparing Classifiers Alsing et al.
11). N11 ¼ 80 þ 2 ¼ 82 N01 ¼ 9 þ 1 ¼ 10 N10 ¼ 0 þ 2 ¼ 2 N00 ¼ 3 þ 3 ¼ 6 From Eq. 841, we reject the null hypothesis and accept that LDC and 9-nn are significantly different. 96, so we cannot reject the null hypothesis and claim that LDC and 9-nn have significantly different accuracies. Which of the two decisions do we trust? The McNemar test takes into account the fact that the same testing set Zts was used whereas the difference of proportions does not. Therefore, we can accept the decision of the McNemar test.
Combining Pattern Classifiers: Methods and Algorithms by Ludmila I. Kuncheva