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"print.randomForest" <-
function(x, ...) {
cat("\nCall:\n", deparse(x$call), "\n")
cat(" Type of random forest: ", x$type, "\n", sep="")
cat(" Number of trees: ", x$ntree, "\n",sep="")
cat("No. of variables tried at each split: ", x$mtry, "\n\n", sep="")
if(x$type == "classification") {
if(!is.null(x$confusion)) {
cat(" OOB estimate of error rate: ",
round(x$err.rate[x$ntree, "OOB"]*100, digits=2), "%\n", sep="")
cat("Confusion matrix:\n")
print(x$confusion)
if(!is.null(x$test$err.rate)) {
cat(" Test set error rate: ",
round(x$test$err.rate[x$ntree, "Test"]*100, digits=2), "%\n",
sep="")
cat("Confusion matrix:\n")
print(x$test$confusion)
}
}
}
if(x$type == "regression") {
if(!is.null(x$mse)) {
cat(" Mean of squared residuals: ", x$mse[length(x$mse)],
"\n", sep="")
cat(" % Var explained: ",
round(100*x$rsq[length(x$rsq)], digits=2), "\n", sep="")
if(!is.null(x$test$mse)) {
cat(" Test set MSE: ",
round(x$test$mse[length(x$test$mse)], digits=2), "\n", sep="")
cat(" % Var explained: ",
round(100*x$test$rsq[length(x$test$rsq)], digits=2), "\n", sep="")
}
}
if (!is.null(x$coefs)) {
cat(" Bias correction applied:\n")
cat(" Intercept: ", x$coefs[1], "\n")
cat(" Slope: ", x$coefs[2], "\n")
}
}
}
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