extractResponse = function(r) {
if (r$getResponseType() == "regression") {
rn = ResponseRegr$new(r)
attr(rn, "positive") = NULL
return(rn)
}
if (r$getResponseType() == "binary_classif") {
rn = ResponseBinaryClassif$new(r)
attr(rn, "positive") = rn$getPositiveClass()
return(rn)
}
stop("Was not able to load response.")
}
extractOptimizer = function(op) {
if (op$getOptimizerType() == "coo_descent") {
return(OptimizerCoordinateDescent$new(op, TRUE))
}
if (op$getOptimizerType() == "coo_descent_ls") {
return(OptimizerCoordinateDescentLineSearch$new(op, TRUE))
}
if (op$getOptimizerType() == "cosine_ann") {
return(OptimizerCosineAnnealing$new(op, TRUE))
}
if (op$getOptimizerType() == "agbm") {
return(OptimizerAGBM$new(op, TRUE, TRUE, TRUE))
}
stop("Was not able to load optimizer.")
}
extractLoss = function(l) {
if (l$getLossType() == "quadratic") {
return(LossQuadratic$new(l, TRUE, TRUE))
}
if (l$getLossType() == "absolute") {
return(LossQuadratic$new(l, TRUE, TRUE))
}
if (l$getLossType() == "quantile") {
return(LossQuadratic$new(l, TRUE, TRUE))
}
if (l$getLossType() == "huber") {
return(LossQuadratic$new(l, TRUE, TRUE))
}
if (l$getLossType() == "binomial") {
return(LossQuadratic$new(l, TRUE, TRUE))
}
stop("Was not able to load optimizer.")
}
extractBaselearnerFactory = function(blf) {
if (blf$getModelName() == "polynomial") {
return(BaselearnerPolynomial$new(blf))
}
if (blf$getModelName() == "pspline") {
return(BaselearnerPSpline$new(blf))
}
if (blf$getModelName() == "tensor") {
return(BaselearnerTensor$new(blf))
}
if (blf$getModelName() == "centered") {
return(BaselearnerCentered$new(blf))
}
if (blf$getModelName() == "cridge") {
return(BaselearnerCategoricalRidge$new(blf))
}
if (blf$getModelName() == "cbinary") {
return(BaselearnerCategoricalBinary$new(blf))
}
stop("Was not able to load factory.")
}
extractData = function(d) {
if (d$getDataType() == "in_memory") {
return(InMemoryData$new(d))
}
if (d$getDataType() == "categorical") {
return(CategoricalDataRaw$new(d))
}
stop("Was not able to load data object.")
}
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