问题
Could anyone provide a simple numeric example of the EM algorithm as I am not sure about the formulas given? A really simple one with 4 or 5 Cartesian coordinates would perfectly do.
回答1:
what about this: http://en.wikibooks.org/wiki/Data_Mining_Algorithms_In_R/Clustering/Expectation_Maximization_(EM)#A_simple_example
I had also written a simple example in (edit)R a year ago, unfortunately I am unable to locate it. I'll try again to find it later.
EDIT: Here it is -
EM <- function() { ### Read file, get necessary cols dataFile <- read.csv("wine.csv", head = FALSE, sep = ",") sl <- dataFile[, 2] #sw <- dataFile[, 3] #pl <- dataFile[, 3] #pw <- dataFile[, 4] class <- dataFile[, 5] N <- length(sl) pi1 <- 0.5 ### Init ### rand1 <- floor(runif(1) * N) rand2 <- floor(runif(1) * N) mu1 <- sl[rand1] mu2 <- sl[rand2] mean1 <- sum(sl)/N sigma1 <- sum( (sl - mean1) ** 2) / N sigma2 <- sigma1 print(mu1) print(mu2) print(sigma1) print(sigma2) COUNTLIM <- 10 count <- 1 prevmu1 <- 0.0; prevmu2 <- 0.0; prevsigma1 <- 0.0; prevsigma2 <- 0.0; gamma <- array(0, length(sl)) while (count <= COUNTLIM) { gamma <- pi1 * dnorm(sl, mu2, sigma2)/ ( (1 - pi1) * dnorm(sl, mu1, sigma1) + pi1 * dnorm(sl, mu2, sigma2)) mu1 <- sum((1 - gamma) * sl) / sum(1 - gamma)
mu2 <- sum((gamma) * sl) / sum(gamma)
sigma1 <- sum((1 - gamma) * (sl - mu1) ** 2)/sum(1 - gamma) sigma2 <- sum((gamma) * (sl - mu2) ** 2)/sum(gamma) pi1 <- sum(gamma)/N print(c(mu1, mu2, sigma1, sigma2, pi1)) if (count == 1) { prevmu1 <- mu1; prevmu2 <- mu2; prevsigma1 <- sigma1; prevsigma2 <- sigma2; } else { val <- ((prevmu1 - mu1)*2 + (prevmu2 - mu2)*2 + (prevsigma1 - sigma1)*2 + (prevsigma2 - sigma2)*2) ** 0.5; print(c("val: " , val)) if (val <= 1) { break; } } count <- count + 1 } print(mu1) print(mu2) print(sigma1) print(sigma2) }
来源:https://stackoverflow.com/questions/14811541/numeric-example-of-the-expectation-maximization-algorithm