version 1.1-7

cran · May 22, 2018 · 1ff4e34 · 1ff4e34
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,17 +1,18 @@
 Package: AppliedPredictiveModeling
 Type: Package
 Title: Functions and Data Sets for 'Applied Predictive Modeling'
-Version: 1.1-6
-Date: 2014-07-24
+Version: 1.1-7
+Date: 2018-05-22
 Author: Max Kuhn, Kjell Johnson
 Maintainer: Max Kuhn <[email protected]>
-Description: A few functions and several data set for the Springer book 'Applied Predictive Modeling'
+Description: A few functions and several data set for the Springer book 'Applied Predictive Modeling'.
 URL: http://appliedpredictivemodeling.com/
 Depends: R (>= 2.10)
-Imports: CORElearn, MASS, plyr, reshape2
-Suggests: caret (>= 6.0-22), lattice, ellipse
-License: GPL
-Packaged: 2014-07-25 13:37:54 UTC; kuhna03
+Imports: CORElearn, MASS, plyr, reshape2, lattice, ellipse
+Suggests: caret (>= 6.0-22)
+License: GPL-2
+RoxygenNote: 6.0.1
 NeedsCompilation: no
+Packaged: 2018-05-22 19:03:00 UTC; max
 Repository: CRAN
-Date/Publication: 2014-07-25 18:42:22
+Date/Publication: 2018-05-22 19:14:21 UTC
diff --git a/MD5 b/MD5
@@ -1,13 +1,14 @@
-b956c4b3e5aad17e35ac120a5d5f59d3 *DESCRIPTION
-03e5df17ec09e62322761dbf70cd3a8a *NAMESPACE
-e4e564d2188913c297d854a86868bd37 *R/bookTheme.R
-538821ec8c21e26d4b936611aa157bc4 *R/easyBoundaryFunc.R
-f4e5463cfcc4da4261f8014b1426c10c *R/getPackages.R
-35a9e06d580a6ed8b8d98c9f3c0a61eb *R/panels.R
-57c3568c0838c1acba62489985f0dea9 *R/permuteRelief.R
-5996be154af6ef121fab077294b2e5e0 *R/quadBoundaryFunc.R
-d35f915bd2268cbb07c258bd8fce5c50 *R/scriptLocation.R
-98d928db47d8347a4f886f0c8e4adde1 *R/transparentTheme.R
+d9a47751fc337024c1a1c41e1da27221 *DESCRIPTION
+f78a4ad513d2c6c72c50fb7c8c3c4fa6 *NAMESPACE
+4ba4117b0411d3dffc0016338e086487 *R/bookTheme.R
+ba7591c480e18250a36afca890626919 *R/easyBoundaryFunc.R
+4bcab4abad6714d7dded5c1bc3924c0c *R/getPackages.R
+4eeffcbe6c341af031b5ca224ddc01e3 *R/panels.R
+2cd8668d7140eff6b9bbb10e281ff643 *R/permuteRelief.R
+f8804618082623af1ab53f6eda5d6c6e *R/quadBoundaryFunc.R
+ea3ad783d73b8ecd91c3df840f944bfe *R/scriptLocation.R
+b7ba633adffdafee73c75abba35be85c *R/transparentTheme.R
+cb9165768774234eeda3f6e724fa4bae *README.md
 8a34126ad3a2f9d077653b26d950dddb *data/AlzheimerDisease.RData
 fe3de40e923db3e0133b269f1610afa2 *data/ChemicalManufacturingProcess.RData
 ef3addd28ad9449688f0c33ba9bfc2d0 *data/FuelEconomy.RData
@@ -21,7 +22,7 @@ e1590269851cf810fdffa832b6cf6d65 *data/schedulingData.RData
 669172e9b524f9194a23fbc84a2816f8 *data/segmentationOriginal.RData
 06780bd86a4db76cb2a8eb12ef107df7 *data/solubility.RData
 5e5422a8c05125f3ab1822f6c525296a *data/twoClassData.RData
-47ca37b7084f35df9345c9c5b6a3d461 *inst/NEWS.Rd
+7973bb1a98c7ee6c2e08604fbd923d59 *inst/NEWS.Rd
 55afb317aa767a6e82c6c52ee985563f *inst/chapters/02_A_Short_Tour.R
 5a487c219abde639b85d7275c6a4bf31 *inst/chapters/02_A_Short_Tour.Rout
 ec4768cf8bf24124e998a1ce680dceb6 *inst/chapters/03_Data_Pre_Processing.R

diff --git a/NAMESPACE b/NAMESPACE
@@ -1,3 +1,8 @@
 exportPattern("^[[:alpha:]]+")
 
 import(CORElearn, MASS, plyr, reshape2)
+importFrom("grDevices", "rgb")
+importFrom("stats", "runif", "sd")
+importFrom("utils", "install.packages")
+importFrom("lattice", "trellis.par.set", "trellis.par.get", "panel.xyplot")
+importFrom("ellipse", "ellipse")
diff --git a/R/bookTheme.R b/R/bookTheme.R
@@ -1,70 +1,75 @@
-bookTheme <- function(set = TRUE)
-  {
-    library(lattice)
-    theme <-    list(plot.polygon = list(alpha = 1, col = "aliceblue", border = "black", lty = 1, lwd = 1),
-                     background = list(col = "transparent"), 
-                     bar.fill = list(col = "#cce6ff"), 
-                     box.rectangle = list(col = "black"), 
-                     box.umbrella = list(col = "black"), 
-                     dot.line = list(col = "#e8e8e8"), 
-                     dot.symbol = list(col = "black"), 
-                     plot.line = list(col = "black", lwd = 1, lty = 1), 
-                     plot.symbol = list(col = "black", pch = 16), 
-                     regions = list(col = 
-                       c("#FEF8FA", "#FDF6F9", "#FBF5F9", "#FAF3F8", 
-                         "#F8F2F7", "#F7F0F7", "#F5EEF6", "#F4EDF5", 
-                         "#F2EBF5", "#F1EAF4", "#EFE8F3", "#EDE7F2", 
-                         "#ECE5F1", "#EAE4F1", "#E8E2F0", "#E6E1EF", 
-                         "#E4DFEE", "#E2DEED", "#E0DCEC", "#DEDAEB", 
-                         "#DCD9EA", "#D9D7E9", "#D7D6E8", "#D4D4E7", 
-                         "#D1D2E6", "#CED1E5", "#CCCFE4", "#C8CEE3",
-                         "#C5CCE2", "#C2CAE1", "#BFC9E0", "#BBC7DF", 
-                         "#B8C5DF", "#B4C4DE", "#B1C2DD", "#ADC0DC", 
-                         "#A9BFDB", "#A6BDDA", "#A2BBD9", "#9EB9D9", 
-                         "#9BB8D8", "#97B6D7", "#93B4D6", "#8FB2D5", 
-                         "#8BB0D4", "#87AFD3", "#83ADD2", "#7FABD1", 
-                         "#7AA9D0", "#76A7CF", "#71A5CE", "#6CA3CC", 
-                         "#68A1CB", "#63A0CA", "#5D9EC9", "#589CC8",
-                         "#539AC6", "#4E98C5", "#4996C4", "#4493C3", 
-                         "#3F91C1", "#3A8FC0", "#358DBF", "#308BBE", 
-                         "#2C89BD", "#2887BC", "#2385BB", "#1F83BA", 
-                         "#1C80B9", "#187EB7", "#157CB6", "#127AB5", 
-                         "#0F78B3", "#0D76B2", "#0A73B0", "#0971AE", 
-                         "#076FAC", "#066DAA", "#056AA7", "#0568A5")
-                       ), 
-                     strip.shingle = list(col = c(
-                                            "#ff7f00", "#00ff00", "#00ffff",
-                                            "#ff00ff", "#ff0000", "#ffff00", "#0080ff")), 
-                     strip.background = list(col = c(
-                                               "#ffe5cc", "#ccffcc", "#ccffff",
-                                               "#ffccff", "#ffcccc", "#ffffcc", "#cce6ff")), 
-                     reference.line = list(col = "#e8e8e8"), 
-                     superpose.line = list(
-                       col = c(
-                         "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
-                         "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
-                         "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black",
-                         "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
-                         "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
-                         "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black"), 
-                       lty = rep(1:6, each = 6)), 
-                     superpose.symbol = list(
-                       pch = c(
-                         1, 4, 6, 0, 5, 17,
-                         4, 6, 0, 5, 17, 1,
-                         6, 0, 5, 17, 1, 4,
-                         0, 5, 17, 1, 4, 6,
-                         5, 17, 1, 4, 6, 0 ,
-                         17, 1, 4, 6, 0, 5), 
-                       cex = rep(0.7,  6 * 6), 
-                       col = c(
-                         "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
-                         "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
-                         "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black",
-                         "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
-                         "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
-                         "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black")))
-
-    if(set) trellis.par.set(theme)
-    invisible(theme)
-  }
+bookTheme <- function(set = TRUE){
+  theme <- list(
+    plot.polygon = list(alpha = 1, col = "aliceblue", border = "black", lty = 1, lwd = 1),
+    background = list(col = "transparent"), 
+    bar.fill = list(col = "#cce6ff"), 
+    box.rectangle = list(col = "black"), 
+    box.umbrella = list(col = "black"), 
+    dot.line = list(col = "#e8e8e8"), 
+    dot.symbol = list(col = "black"), 
+    plot.line = list(col = "black", lwd = 1, lty = 1), 
+    plot.symbol = list(col = "black", pch = 16), 
+    regions = list(col = 
+                     c("#FEF8FA", "#FDF6F9", "#FBF5F9", "#FAF3F8", 
+                       "#F8F2F7", "#F7F0F7", "#F5EEF6", "#F4EDF5", 
+                       "#F2EBF5", "#F1EAF4", "#EFE8F3", "#EDE7F2", 
+                       "#ECE5F1", "#EAE4F1", "#E8E2F0", "#E6E1EF", 
+                       "#E4DFEE", "#E2DEED", "#E0DCEC", "#DEDAEB", 
+                       "#DCD9EA", "#D9D7E9", "#D7D6E8", "#D4D4E7", 
+                       "#D1D2E6", "#CED1E5", "#CCCFE4", "#C8CEE3",
+                       "#C5CCE2", "#C2CAE1", "#BFC9E0", "#BBC7DF", 
+                       "#B8C5DF", "#B4C4DE", "#B1C2DD", "#ADC0DC", 
+                       "#A9BFDB", "#A6BDDA", "#A2BBD9", "#9EB9D9", 
+                       "#9BB8D8", "#97B6D7", "#93B4D6", "#8FB2D5", 
+                       "#8BB0D4", "#87AFD3", "#83ADD2", "#7FABD1", 
+                       "#7AA9D0", "#76A7CF", "#71A5CE", "#6CA3CC", 
+                       "#68A1CB", "#63A0CA", "#5D9EC9", "#589CC8",
+                       "#539AC6", "#4E98C5", "#4996C4", "#4493C3", 
+                       "#3F91C1", "#3A8FC0", "#358DBF", "#308BBE", 
+                       "#2C89BD", "#2887BC", "#2385BB", "#1F83BA", 
+                       "#1C80B9", "#187EB7", "#157CB6", "#127AB5", 
+                       "#0F78B3", "#0D76B2", "#0A73B0", "#0971AE", 
+                       "#076FAC", "#066DAA", "#056AA7", "#0568A5")
+    ), 
+    strip.shingle = list(col = c(
+      "#ff7f00", "#00ff00", "#00ffff",
+      "#ff00ff", "#ff0000", "#ffff00", "#0080ff")
+    ), 
+    strip.background = list(col = c(
+      "#ffe5cc", "#ccffcc", "#ccffff",
+      "#ffccff", "#ffcccc", "#ffffcc", "#cce6ff")
+    ), 
+    reference.line = list(col = "#e8e8e8"), 
+    superpose.line = list(
+      col = c(
+        "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
+        "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
+        "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black",
+        "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
+        "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
+        "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black"
+      ), 
+      lty = rep(1:6, each = 6)), 
+    superpose.symbol = list(
+      pch = c(
+        1, 4, 6, 0, 5, 17,
+        4, 6, 0, 5, 17, 1,
+        6, 0, 5, 17, 1, 4,
+        0, 5, 17, 1, 4, 6,
+        5, 17, 1, 4, 6, 0 ,
+        17, 1, 4, 6, 0, 5), 
+      cex = rep(0.7,  6 * 6), 
+      col = c(
+        "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
+        "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
+        "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black",
+        "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
+        "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black", 
+        "#053061", "#B2182B", "#F46D43", "#5E4FA2", "#66C2A5", "black"
+      )
+    )
+  )
+
+  if(set) trellis.par.set(theme)
+  invisible(theme)
+}
diff --git a/R/easyBoundaryFunc.R b/R/easyBoundaryFunc.R
@@ -1,15 +1,20 @@
 
-easyBoundaryFunc <- function(n, intercept = 0, interaction = 2)
-{
-   sigma <- matrix(c(2,1.3,1.3,2),2,2)
-
-   tmpData <- data.frame(mvrnorm(n=n, c(0,0), sigma))
-   xSeq <- seq(-4, 4, length=40)
-   plotGrid <- expand.grid(x = xSeq, y = xSeq)
-   zFoo <- function(x, y) intercept -4 * x + 4* y + interaction*x*y
-   z2p <- function(x) 1/(1+exp(-x))
-
-   tmpData$prob <- z2p(zFoo(tmpData$X1, tmpData$X2))
-   tmpData$class <- factor(ifelse(runif(length(tmpData$prob)) <= tmpData$prob, "Class1", "Class2"))
-   tmpData
+
+easyBoundaryFunc <- function(n,
+                             intercept = 0,
+                             interaction = 2) {
+  sigma <- matrix(c(2, 1.3, 1.3, 2), 2, 2)
+
+  tmpData <- data.frame(mvrnorm(n = n, c(0, 0), sigma))
+  xSeq <- seq(-4, 4, length = 40)
+  plotGrid <- expand.grid(x = xSeq, y = xSeq)
+  zFoo <- function(x, y)
+    intercept - 4 * x + 4 * y + interaction * x * y
+  z2p <- function(x)
+    1 / (1 + exp(-x))
+
+  tmpData$prob <- z2p(zFoo(tmpData$X1, tmpData$X2))
+  tmpData$class <-
+    factor(ifelse(runif(length(tmpData$prob)) <= tmpData$prob, "Class1", "Class2"))
+  tmpData
 }
diff --git a/R/getPackages.R b/R/getPackages.R
@@ -1,8 +1,8 @@
 
 
-getPackages <- function(chapter, ...)
-{
-  if(is.numeric(chapter)) chapter <- paste(chapter)
+getPackages <- function(chapter, ...) {
+  if(is.numeric(chapter)) 
+    chapter <- paste(chapter)
   pkg <- list()
   pkg[["2"]] <- c("earth", "caret", "lattice")
   pkg[["3"]] <- c("e1071", "caret", "corrplot")
@@ -30,16 +30,16 @@ getPackages <- function(chapter, ...)
   pkg[["18"]] <- c("caret", "CORElearn", "corrplot", "pROC", "minerva")
   pkg[["19"]] <- c("caret", "MASS", "corrplot", "RColorBrewer", "randomForest", 
                    "kernlab", "klaR")
-  plist <- paste(paste("'", names(pkg), "'", sep = ""), collapse = ", ")
-  if(!any(chapter %in% names(pkg))) stop(paste("'chapter' must be: ",
-                                               paste(plist, collapse = ", ")),
-                                         sep = "")  
-
+  plist <-
+    paste(paste("'", names(pkg), "'", sep = ""), collapse = ", ")
+  if (!any(chapter %in% names(pkg)))
+    stop(paste("'chapter' must be: ",
+               paste(plist, collapse = ", ")))  
 
   pkg <- unlist(pkg[chapter])
   pkg <- pkg[!is.na(pkg)]
   pkg <- pkg[pkg != ""]
   pkg <- pkg[order(tolower(pkg))]
-
+  
   install.packages(pkg, ...)
 }
diff --git a/R/panels.R b/R/panels.R
@@ -1,30 +1,38 @@
-upperp <- function(...)
-  {
-    library(ellipse)
-    args <- list(...)
-    circ1 <- ellipse(diag(rep(1, 2)), t = .1)
-    panel.xyplot(circ1[,1], circ1[,2],
-                 type = "l",
-                 lty = trellis.par.get("reference.line")$lty,
-                 col = trellis.par.get("reference.line")$col,
-                 lwd = trellis.par.get("reference.line")$lwd)
-    circ2 <- ellipse(diag(rep(1, 2)), t = .2)
-    panel.xyplot(circ2[,1], circ2[,2],
-                 type = "l",
-                 lty = trellis.par.get("reference.line")$lty,
-                 col = trellis.par.get("reference.line")$col,
-                 lwd = trellis.par.get("reference.line")$lwd)
-    circ3 <- ellipse(diag(rep(1, 2)), t = .3)
-    panel.xyplot(circ3[,1], circ3[,2],
-                 type = "l",
-                 lty = trellis.par.get("reference.line")$lty,
-                 col = trellis.par.get("reference.line")$col,
-                 lwd = trellis.par.get("reference.line")$lwd)
-    panel.xyplot(args$x, args$y, groups = args$groups, subscripts = args$subscripts)
-  }
-
-lowerp <- function(...)
-  {
-
-  }
+upperp <- function(...) {
+  args <- list(...)
+  circ1 <- ellipse(diag(rep(1, 2)), t = .1)
+  panel.xyplot(
+    circ1[, 1],
+    circ1[, 2],
+    type = "l",
+    lty = trellis.par.get("reference.line")$lty,
+    col = trellis.par.get("reference.line")$col,
+    lwd = trellis.par.get("reference.line")$lwd
+  )
+  circ2 <- ellipse(diag(rep(1, 2)), t = .2)
+  panel.xyplot(
+    circ2[, 1],
+    circ2[, 2],
+    type = "l",
+    lty = trellis.par.get("reference.line")$lty,
+    col = trellis.par.get("reference.line")$col,
+    lwd = trellis.par.get("reference.line")$lwd
+  )
+  circ3 <- ellipse(diag(rep(1, 2)), t = .3)
+  panel.xyplot(
+    circ3[, 1],
+    circ3[, 2],
+    type = "l",
+    lty = trellis.par.get("reference.line")$lty,
+    col = trellis.par.get("reference.line")$col,
+    lwd = trellis.par.get("reference.line")$lwd
+  )
+  panel.xyplot(args$x,
+               args$y,
+               groups = args$groups,
+               subscripts = args$subscripts)
+}
 
+lowerp <- function(...) {
+
+}
diff --git a/R/permuteRelief.R b/R/permuteRelief.R
@@ -1,25 +1,24 @@
 permuteRelief <-
-function(x, y, nperm = 100, ...)
-  {
+  function(x, y, nperm = 100, ...) {
     dat <- x
     dat$y <- y
 
     obs <- attrEval(y ~ ., data = dat, ...)
     permuted <- matrix(NA, ncol = length(obs), nrow = nperm)
     colnames(permuted) <- names(obs)
-    for(i in 1:nperm)
-      {
-        dat$y <- sample(y)
-        permuted[i,] <- attrEval(y ~ ., data = dat, ...)
-      }
+    for (i in 1:nperm) {
+      dat$y <- sample(y)
+      permuted[i,] <- attrEval(y ~ ., data = dat, ...)
+    }
     means <- colMeans(permuted)
     sds <- apply(permuted, 2, sd)
     permuted <- melt(permuted)
     names(permuted)[2] <- "Predictor"
     permuted$X1 <- NULL
-    list(standardized = (obs - means)/sds,
-         permutations = permuted,
-         observed = obs,
-         options = list(...))
+    list(
+      standardized = (obs - means) / sds,
+      permutations = permuted,
+      observed = obs,
+      options = list(...)
+    )
   }
-