BenchmarkEva: Title Benchmark calculation In particular unique combination...

In yujijun/neoantigenML: Machine Learning Methods for Neoantigen Filtering

Title Benchmark calculation In particular unique combination of Task,Learner and Resampling.

Description

Title Benchmark calculation In particular unique combination of Task,Learner and Resampling.

Usage

BenchmarkEva(tasks, learners, resamplings = "none")

Arguments

tasks	A vector of task
learners	A list of learners
resamplings	A resamplings methods

Examples

design = benchmark_grid(
tasks = tsks(c("spam", "german_credit", "sonar")),
learners = lrns(c("classif.glmnet", "classif.rpart", "classif.featureless"),
               predict_type = "prob", predict_sets = c("train", "test")),
resamplings = rsmps("cv", folds = 3)
classif.glmnet.rbv2,classif.kknn.rbv2,classif.ranger.rbv2,classif.svm.rbv2,classif.xgboost.rbv2,

yujijun/neoantigenML documentation built on March 20, 2022, 11:59 p.m.