Nothing
lift <- function(x, ...) UseMethod("lift")
lift.default <- function(x, ...) stop("'x' should be a formula")
lift.formula <- function(x, data = NULL, class = NULL,subset = TRUE, lattice.options = NULL, labels = NULL, ...)
{
if (!is.null(lattice.options)) {
oopt <- lattice.options(lattice.options)
on.exit(lattice.options(oopt), add = TRUE)
}
formula <- x
groups <- NULL
subset <- eval(substitute(subset), data, environment(x))
form <- latticeParseFormula(formula, data, subset = subset,
groups = groups, multiple = TRUE, outer = TRUE,
subscripts = TRUE, drop = TRUE)
liftData <- data.frame(prob = form$y)
probNames <- strsplit(form$right.name, " + ", fixed = TRUE)[[1]]
if(!is.null(labels))
{
if(length(labels) != length(probNames)) stop("labels should have an element for each term on the rhs of the formula")
if(!all(probNames %in% names(labels))) stop(paste("labels should be a named vector or list with names:",
paste(probNames, collapse = ", ")))
}
liftData <- data.frame(liftClassVar = rep(form$left, length(probNames)),
liftProbVar = form$right)
liftData$liftModelVar <- if(length(probNames) > 1) form$condition[[length(form$condition)]] else probNames
if(length(form$condition) > 0 && any(names(form$condition) != ""))
{
ind <- sum(names(form$condition) != "")
tmp <- as.data.frame(form$condition[1:ind])
liftData <- cbind(liftData, tmp)
}
if(!is.factor(liftData$liftClassVar)) stop("the left-hand side of the formula must be a factor of classes")
splitVars <- names(liftData)[!(names(liftData) %in% c("liftClassVar", "liftProbVar"))]
if(is.null(class)) class <- levels(liftData$liftClassVar)[1]
plotData <- ddply(liftData, splitVars, liftCalc, class = class)
if(!is.null(labels))
{
plotData$originalName <- plotData$liftModelVar
plotData$liftModelVar <- as.character(plotData$liftModelVar)
for(i in seq(along = labels)) plotData$liftModelVar[plotData$liftModelVar == names(labels)[i]] <- labels[i]
plotData$liftModelVar <- factor(plotData$liftModelVar,
levels = labels)
}
out <- list(data = plotData, class = class, probNames = probNames,
pct = mean(liftData$liftClassVar == class)*100, call = match.call())
class(out) <- "lift"
out
}
print.lift <- function(x, ...)
{
printCall(x$call)
cat("Models:", paste(unique(x$data$liftModelVar), collapse = ", "), "\n")
cat("Event: ", x$class, " (", round( x$pct, 1), "%)\n", sep = "")
invisible(x)
}
plot.lift <- function(x, y = NULL, ...) xyplot.lift(x = x, data = NULL, ...)
xyplot.lift <- function(x, data = NULL, plot = "gain", values = NULL, ...)
{
if(!(plot %in% c("lift", "gain"))) stop(paste("'plot' should be either 'lift' or 'gain'"))
if(plot == "gain")
{
lFormula <- "CumEventPct ~ CumTestedPct"
rng <- extendrange(c(0, 100))
opts <- list(...)
if(!any(names(opts) == "xlab")) opts$xlab <- "% Samples Tested"
if(!any(names(opts) == "ylab")) opts$ylab <- "% Samples Found"
if(!any(names(opts) == "type")) opts$type <- "l"
if(!any(names(opts) == "ylim")) opts$ylim <- rng
if(!any(names(opts) == "xlim")) opts$xlim <- rng
if(!any(names(opts) == "panel")) opts$panel <- panel.lift2
} else {
lFormula <- "lift ~ cuts"
x$data <- x$data[order(x$data$liftModelVar, x$data$cuts),]
rng <- extendrange(c(0, 100))
opts <- list(...)
if(!any(names(opts) == "xlab")) opts$xlab <- "Cut-Off"
if(!any(names(opts) == "ylab")) opts$ylab <- "Lift"
if(!any(names(opts) == "type")) opts$type <- "l"
}
args <- list(x = as.formula(lFormula),
data = x$data,
pct = x$pc,
values = values)
if(length(x$probNames) > 1) args$groups <- x$data$liftModelVar
args <- c(args, opts)
do.call("xyplot", args)
}
liftCalc <- function(x, class = levels(x$liftClassVar)[1])
{
lvl <- levels(x$liftClassVar)
x <- x[order(x$liftProbVar, decreasing = TRUE),]
nEvents <- sum(x$liftClassVar == class)
baseline <- mean(x$liftClassVar == class)
cuts <- sort(unique(x$liftProbVar), decreasing = TRUE)
cuts <- unique(c(1, cuts, 0))
class2 <- levels(x$liftClassVar)
class2 <- class2[class2 != class]
tmp <- data.frame(cuts = cuts,
events = NA,
n = NA,
Sn = NA,
Sp = NA)
for(i in seq(along = cuts))
{
sub <- x$liftClassVar[x$liftProbVar >= tmp$cuts[i]]
tmp$n[i] <- length(sub)
tmp$events[i] <- sum(sub == class)
prd <- factor(ifelse(x$liftProbVar >= tmp$cuts[i], class, class2),
levels = levels(x$liftClassVar))
tmp$Sn[i] <- sensitivity(prd,
x$liftClassVar,
positive = class)
tmp$Sp[i] <- specificity(prd,
x$liftClassVar,
negative = class2)
}
tmp$EventPct <- ifelse(tmp$n > 0, tmp$events/tmp$n*100, 0)
tmp$CumEventPct <- tmp$events/nEvents*100
tmp$lift <- tmp$events/tmp$n/baseline
tmp$CumTestedPct <- tmp$n/nrow(x)*100
tmp
}
panel.lift <- function(x, y, ...)
{
panel.xyplot(x, y, ...)
panel.abline(0, 1, col = "black")
}
panel.lift2 <- function (x, y, pct = 0, values = NULL, ...)
{
polyx <- c(0, pct, 100, 0)
polyy <- c(0, 100, 100, 0)
regionStyle <- trellis.par.get("reference.line")
panel.polygon(polyx, polyy,
col = regionStyle$col,
border = regionStyle$col)
panel.xyplot(x, y, ...)
if(!is.null(values))
{
theDots <- list(...)
if(any(names(theDots) == "groups"))
{
dat <- data.frame(x = x, y = y, groups = theDots$groups)
ung <- unique(dat$groups)
for(i in seq(along = ung))
{
dat0 <- subset(dat, groups == ung[i])
plotRef(dat0$x, dat0$y, values, iter = i)
}
} else plotRef(x, y, values)
}
}
plotRef <- function(x, y, v, iter = 0)
{
if(iter == 0) {
lineStyle <- trellis.par.get("plot.line")
} else {
lineStyle <- trellis.par.get("superpose.line")
lineStyle <- lapply(lineStyle, function(x, i) x[min(length(x), i)], i = iter)
}
erx <- extendrange(x)
ery <- extendrange(y)
values <- approx(y, x, xout = v)
for(i in seq(along = values$x)) {
panel.segments(values$y[i], ery[1], values$y[i], values$x[i],
lty = lineStyle$lty, col = lineStyle$col,
alpha = lineStyle$alpha, lwd = lineStyle$lwd)
panel.segments(erx[1], values$x[i], values$y[i], values$x[i],
lty = lineStyle$lty, col = lineStyle$col,
alpha = lineStyle$alpha, lwd = lineStyle$lwd)
}
}
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