Nothing
LearnerList <- list(
"constparty" = list(
class = "constparty",
package = "partykit",
predict = function(x, newdata, yclass = NULL) {
type <- ifelse(match(yclass, c("ordered", "factor"), nomatch = FALSE), "prob", "response")
predict(x, newdata = newdata, type = type)
}
),
"cforest" = list(
class = "cforest",
package = "partykit",
predict = function(x, newdata, yclass = NULL) {
type <- ifelse(match(yclass, c("ordered", "factor"), nomatch = FALSE), "prob", "response")
predict(x, newdata = newdata, type = type)
}
),
"rpart" = list(
class = "rpart",
package = "rpart",
predict = function(x, newdata, yclass = NULL) {
type <- ifelse(match(yclass, c("ordered", "factor"), nomatch = FALSE), "prob", "vector")
predict(x, newdata = newdata, type = type)
}
),
"J48" = list(
class = "J48",
package = "RWeka",
predict = function(x, newdata, yclass = NULL) {
type <- ifelse(match(yclass, c("ordered", "factor"), nomatch = FALSE), "prob", "class")
predict(x, newdata = newdata, type = type)
}
),
"C5.0" = list(
class = "C5.0",
package = "C50",
predict = function(x, newdata, yclass = NULL) {
type <- ifelse(match(yclass, c("ordered", "factor"), nomatch = FALSE), "prob", "class")
predict(x, newdata = newdata, type = type)
}
),
"tree" = list(
class = "tree",
package = "tree",
predict = function(x, newdata, yclass = NULL) {
predict(x, newdata = newdata, type = "vector")
}
),
"randomForest" = list(
class = "randomForest",
package = "randomForest",
predict = function(x, newdata, yclass = NULL) {
type <- ifelse(match(yclass, c("ordered", "factor"), nomatch = FALSE), "prob", "response")
predict(x, newdata = newdata, type = type)
}
),
"svm" = list(
class = "svm",
package = "e1071",
predict = function(x, newdata, yclass = NULL) {
if(match(yclass, c("ordered", "factor"))) {
attr(predict(x, newdata = newdata, probability = TRUE), "probabilities")
} else {
predict(x, newdata = newdata)
}
}
),
"ksvm" = list(
class = "ksvm",
package = "kernlab",
predict = function(x, newdata, yclass = NULL) {
if(match(yclass, c("ordered", "factor"))) {
predict(x, newdata = newdata, type = "probabilities")
} else {
predict(x, newdata = newdata)
}
},
update = function(x, data = NULL, weights = NULL) {
if(!is.null(weights)) stop("Weights are not supported for this class. Please use data argument.")
call <- as.list(x@kcall)[-1]
call$x <- formula(x@terms)
call$data <- data
do.call("ksvm", call)
}
),
"mboost" = list(
class = "mboost",
package = "mboost",
predict = function(x, newdata, yclass = NULL) {
p <- predict(x, newdata = newdata, type = "response")
return(p)
},
update = function(x, data = NULL, weights = NULL) {
call <- as.list(getCall(x))[-1]
call$data <- data
call$weights <- weights
do.call("mboost", call)
}
),
"boosting" = list(
class = "boosting",
package = "adabag",
predict = function(x, newdata, yclass = NULL) {
predict(x, newdata = newdata)$prob
}
),
"adaboost" = list(
class = "adaboost",
package = "fastAdaboost",
predict = function(x, newdata, yclass = NULL) {
predict(x, newdata = newdata)$prob
}
),
"gbm" = list(
class = "gbm",
package = "gbm",
predict = function(x, newdata, yclass = NULL) {
predict(x, newdata = newdata, n.trees = x$n.trees, type = "response")[,,1]
},
terms = function(x) x$Terms
),
"nnet" = list(
class = "nnet",
package = "nnet",
predict = function(x, newdata, yclass = NULL) {
predict(x, newdata = newdata, type = "raw")
}
),
"multinom" = list(
class = "multinom",
package = "nnet",
predict = function(x, newdata, yclass = NULL) {
predict(x, newdata = newdata, type = "probs")
}
),
"lda" = list(
class = "lda",
package = "MASS",
predict = function(x, newdata, yclass = NULL) {
predict(x, newdata = newdata)$posterior
}
),
"lm" = list(
class = "lm",
package = "stats",
predict = function(x, newdata, yclass = NULL) {
predict(x, newdata = newdata)
}
),
"glm" = list(
class = "glm",
package = "stats",
predict = function(x, newdata, yclass = NULL) {
predict(x, newdata = newdata, type = "response")
}
),
"glmrob" = list(
class = "glmrob",
package = "robustbase",
predict = function(x, newdata, yclass = NULL) {
predict(x, newdata = newdata, type = "response")
}
),
"glmnet.formula" = list(
class = "glmnet.formula",
package = "glmnetUtils",
predict = function(x, newdata, yclass = NULL) {
p <- predict(x, newdata = newdata, type = "response")
if(getCall(x)$family == "multinomial") p <- p[,,1]
return(p)
},
update = function(x, data = NULL, weights = NULL) {
call <- as.list(getCall(x))[-1]
call$data <- data
call$weights <- weights
do.call("glmnet.formula", call, envir = asNamespace("glmnetUtils"))
}
)
)
## getCal function for constparties
getCall.cforest <- function(x, ...) x$info$call
## getCall function for class ksvm
# getCall.ksvm <- function(object) {
# call <- as.list(x@kcall)
# call[[1]] <- as.symbol("ksvm")
# call$x <- formula(x@terms)
# call$data = NULL
# return(as.call(call))
# }
# save("LearnerList", file = "sysdata.rda")
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