lhdTuner

task configuration for tuning algorithm

confFile

theSpotPath

envT

the <code><a rd-options="" href="/link/TDMdata?package=TDMR&version=2.2" data-mini-rdoc="TDMR::TDMdata">TDMdata</a></code> object containing the data set (train/vali part and test part)

dataObj

Perform a parameter tuning using a Latin hypercube design (LHD) 
for obtaining best design points. LHD is performed by configuring SPOT 
in such a way that all the budget is used for the initial design (usually LHD).

internal

Tuned Data Mining in R ('TDMR') performs the complete tuning of a
data mining task (predictive analytics, that is classification and regression).
Preprocessing parameters and modeling parameters can be tuned simultaneously.
It incorporates a variety of tuners (among them 'SPOT' and 'CMA' with package 'rCMA') and
allows integration of additional tuners. Noise handling in the data mining optimization
process is supported, see Koch et al. (2015) <doi:10.1016/j.asoc.2015.01.005>.

Wolfgang Konen

TDMR

Tuned Data Mining in R

lhdTuner function

the <code><a rd-options='' href='TDMdata'>TDMdata</a></code> object containing the data set (train/vali part and test part)

lhdTuner: Perform LHD tuning.

Description

Usage

Arguments

Value