RemixAutoML (version 0.4.2)

CatBoostParameterGrids: CatBoostParameterGrids

Description

CatBoostParameterGrids https://catboost.ai/docs/concepts/r-training-parameters.html

Usage

CatBoostParameterGrids(
  TaskType = "CPU",
  Shuffles = 1L,
  NTrees = seq(1000L, 10000L, 1000L),
  Depth = seq(4L, 16L, 2L),
  LearningRate = c(0.01, 0.02, 0.03, 0.04),
  L2_Leaf_Reg = seq(1, 10, 1),
  RandomStrength = seq(1, 2, 0.1),
  BorderCount = seq(32, 256, 32),
  RSM = c(0.8, 0.85, 0.9, 0.95, 1),
  BootStrapType = c("Bayesian", "Bernoulli", "Poisson", "MVS", "No"),
  GrowPolicy = c("SymmetricTree", "Depthwise", "Lossguide")
)

Arguments

TaskType

"GPU" or "CPU"

Shuffles

The number of shuffles you want to apply to each grid

NTrees

seq(1000L, 10000L, 1000L)

Depth

seq(4L, 16L, 2L)

LearningRate

seq(0.01,.10,0.01)

L2_Leaf_Reg

c(1.0:10.0)

RandomStrength

seq(1, 2, 0.1)

BorderCount

seq(32,256,32)

RSM

CPU ONLY, Random subspace method.c(0.80, 0.85, 0.90, 0.95, 1.0)

BootStrapType

c("Bayesian", "Bernoulli", "Poisson", "MVS", "No")

GrowPolicy

c("SymmetricTree", "Depthwise", "Lossguide")

Value

A list containing data.table's with the parameters shuffled and ready to test in the bandit framework

See Also

Other Supervised Learning: AutoH2OScoring(), CatBoostClassifierParams(), CatBoostMultiClassParams(), CatBoostRegressionParams(), XGBoostClassifierParams(), XGBoostMultiClassParams(), XGBoostParameterGrids(), XGBoostRegressionMetrics(), XGBoostRegressionParams()