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2. Let , = P(Y = j) be the prior membership probability Write down the expression of the unnormalized and untransformed theoretical (population) Bayes discriminant function 6,(x) for group

2. Let , = P(Y = j) be the prior membership probability Write down the expression of the unnormalized and untransformed theoretical (population) Bayes discriminant function 6,(x) for group

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.4: Distributions Of Data
Problem 19PFA
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Please solve only 2nd question

2. Let n; = P(Y = j) be the prior membership probability Write down the expression of the unnormalized and untransformed theoretical (population) Bayes discriminant function 6,(x) for group %3! 3. Consider n, = E, I(Y, = j), where n is the number of observations in the data. Write the estimator , of n, as a function of n. %3! %3D 4. Kernel density Estimation for class conditional densities: • Explain the typical procedure that can be used to help derive the isotropic bandwidth matrix from Scott's rule of thumb. • Write down the mathematical expression of the estimator 6,(x) of the Bayes discrim- inant function for each of the classes when the class conditional is a nonparametric kernel density estimator
Transcribed Image Text:2. Let n; = P(Y = j) be the prior membership probability Write down the expression of the unnormalized and untransformed theoretical (population) Bayes discriminant function 6,(x) for group %3! 3. Consider n, = E, I(Y, = j), where n is the number of observations in the data. Write the estimator , of n, as a function of n. %3! %3D 4. Kernel density Estimation for class conditional densities: • Explain the typical procedure that can be used to help derive the isotropic bandwidth matrix from Scott's rule of thumb. • Write down the mathematical expression of the estimator 6,(x) of the Bayes discrim- inant function for each of the classes when the class conditional is a nonparametric kernel density estimator
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