## ----eval=FALSE, message=FALSE, warning=FALSE--------------------------------- # install.packages("ppclust") ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- library(ppclust) ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- library(factoextra) library(cluster) library(fclust) ## ----echo=TRUE, message=FALSE, warning=FALSE, cols.print=5, rows.print=10----- data(iris) x=iris[,-5] x ## ----fig.width=7, fig.height=6------------------------------------------------ pairs(x, col=iris[,5]) ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- res.upfc <- upfc(x, centers=3) ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- v0 <- matrix(nrow=3, ncol=4, c(5.0, 3.4, 1.4, 0.3, 6.7, 3.0, 5.6, 2.1, 5.8, 2.7, 4.3, 1.4), byrow=TRUE) print(v0) res.upfc <- upfc(x, centers=v0) ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- v0 <- inaparc::kmpp(x, k=3)$v print(v0) res.upfc <- upfc(x, centers=v0) ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- u0 <- inaparc::imembrand(nrow(x), k=3)$u res.upfc <- upfc(x, centers=3, memberships=u0) ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- res.upfc <- upfc(x, centers=3, alginitv="firstk", alginitu="imembrand") ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- res.upfc <- upfc(x, centers=3, dmetric="euclidean") ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- res.upfc <- upfc(x, centers=3, m=4) ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- res.upfc <- upfc(x, centers=3, eta=3) ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- res.upfc <- upfc(x, centers=3, a=3, b=2) ## ----echo=TRUE, message=FALSE, warning=FALSE, cols.print=3, rows.print=10----- res.upfc <- upfc(x, centers=3) as.data.frame(res.upfc$u) ## ----echo=TRUE, message=FALSE, warning=FALSE, cols.print=3, rows.print=10----- as.data.frame(res.upfc$t) ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- res.upfc$v0 res.upfc$v ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- summary(res.upfc) ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- res.upfc$comp.time ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- res.upfc <- upfc(x, centers=3, nstart=4) ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- res.upfc <- upfc(x, centers=3, nstart=4, fixmemb=TRUE) ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- res.upfc$func.val res.upfc$iter res.upfc$comp.time ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- res.upfc$best.start ## ----echo=FALSE, message=FALSE, warning=FALSE--------------------------------- res.upfc <- upfc(x, centers=3) ## ----echo=TRUE, message=FALSE, warning=FALSE---------------------------------- summary(res.upfc) ## ----fig.width=7, fig.height=6------------------------------------------------ plotcluster(res.upfc, cp=1, trans=TRUE) ## ----fig.width=7, fig.height=6------------------------------------------------ plotcluster(res.upfc, cp=1, tv=0.25, trans=TRUE) ## ----fig.width=7, fig.height=6------------------------------------------------ plotcluster(res.upfc, mt="u", cp=1, trans=TRUE) ## ----fig.width=7, fig.height=6------------------------------------------------ res.upfc2 <- ppclust2(res.upfc, "kmeans") factoextra::fviz_cluster(res.upfc2, data = x, ellipse.type = "convex", palette = "jco", repel = TRUE) ## ----fig.width=7, fig.height=6------------------------------------------------ res.upfc3 <- ppclust2(res.upfc, "fanny") cluster::clusplot(scale(x), res.upfc3$cluster, main = "Cluster plot of Iris data set", color=TRUE, labels = 2, lines = 2, cex=1) ## ----------------------------------------------------------------------------- res.upfc4 <- ppclust2(res.upfc, "fclust") idxsf <- SIL.F(res.upfc4$Xca, res.upfc4$U, alpha=1) idxpe <- PE(res.upfc4$U) idxpc <- PC(res.upfc4$U) idxmpc <- MPC(res.upfc4$U) ## ----------------------------------------------------------------------------- cat("Partition Entropy: ", idxpe) cat("Partition Coefficient: ", idxpc) cat("Modified Partition Coefficient: ", idxmpc) cat("Fuzzy Silhouette Index: ", idxsf)