Learn R Programming

TDMR (version 2.2)

Tuned Data Mining in R

Description

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) .

Copy Link

Version

Install

install.packages('TDMR')

Monthly Downloads

22

Version

2.2

License

GPL (>= 2)

Maintainer

Wolfgang Konen

Last Published

March 2nd, 2020

Functions in TDMR (2.2)

Default settings for the spotConfig part of TDMR.

Perform CMA-ES tuning (Java version).

Default settings for the data mining part of TDMR (list opts).

Perform CMA-ES tuning (R version).

Return the list 'opts'.

Output objects to cat if opts$VERBOSE>=2.

Return test data

Output objects to cat if opts$VERBOSE>=1.

Perform BFGS tuning.

dsetTest.TDMdata

Return test data of TDMdata object

Tuned Data Mining in R

print.TDMregressor

Print an overview for a TDMregressor object.

makeTdmRandomSeed

Factory method to make a function generating pseudo-random random number seeds.

Print objects using print if opts$VERBOSE>=1.

Return train-validataion data

dsetTrnVa.TDMdata

Return train-validation data of TDMdata object

Perform LHD tuning.

Tuning and unbiased evaluation in a big loop.

Perform a SPOT tuning.

predict.TDMenvir

Make a prediction using the last model.

Construct a new environment envT of class TDMenvir.

tdmDefaultsFill

Default values for list tdm.

Make a report plot based on envT

tdmDispatchTuner

Helper function for tdmBigLoop.

tdmGraphicCloseWin

Close active file ("png").

tdmBindResponse

Bind a column to a data frame.

print.TDMclassifier

Print an overview for a TDMclassifier object.

tdmEnvTAddBstRes

Add BST and RES data frames to an existing envT environment.

Update envT$tdm

Core classification function of TDMR.

Print an overview for a TDMdata object.

tdmEnvTAddGetters

Add getter functions getBst and getRes to environment envT

Set list opts for the k-th element of envT$sCList

tdmGraAndLogInitialize

Initialize graphics and log file.

tdmGraphicCloseDev

Close all open graphic devices.

tdmEnvTReportSens

Function to generate a report with sensitivity plot.

tdmClassifySummary

Print summary output for result from tdmClassifiyLoop and add result$y.

tdmPreNAroughfix

Replace <NA> values with suitable non <NA> values

tdmClassifyLoop

Core classification double loop returning a TDMclassifier object.

Initialize graphic device.

tdmPreLevel2Target

Relate levels of a column with a target (column).

Apply the mapping from des to opts.

tdmParaBootstrap

Parametric bootstrap: add 'noisy copies' to a data frame (training data).

tdmOptsDefaultsSet

Default values for list opts.

tdmOptsDefaultsFill

Fill the current opts.

Merge the parameters from a partial list and the default list

tdmROCR.TDMclassifier

Interactive plot of ROC, lift or other charts for a TDMclassifier object.

tdmModCreateCVindex

Create and return a training-validation-set index vector.

tdmPrePCA.apply

Apply PCA (Principal Component Analysis) to new data.

Interactive plot of ROC charts

tdmPreFindConstVar

Find constant columns.

Print objects using print if opts$VERBOSE>=2.

just to make example check happy

Perform unbiased runs with best-solution parameters.

Single plot of ROC, lift or other chart for a TDMclassifier object.

tdmPreAddMonomials

Add monomials of degree 2 to a data frame.

Load the mapping files.

tdmGraAndLogFinalize

Finalize graphics and log file

Calculate confusion matrix, gain and RGain measure.

tdmPreSFA.apply

Apply SFA (Slow Feature Analysis) to new data.

Generates pseudo-random random number seeds.

Tuning and unbiased evaluation (single tuning).

Return list opts from the k-th element of envT$sCList

tdmModSortedRFimport

Sort the input variables decreasingly by their RF-importance.

tdmGraphicNewWin

Initialize a new window.

tdmModVote2Target

Analyze how the vote fraction corresponds to reliability of prediction.

Load an envT-type environment from file fileRData.

tdmGraphicToTop

Bring the acitve window to the top

tdmPrePCA.train

PCA (Principal Component Analysis) for numeric columns in a data frame.

Core regression double loop returning a TDMregressor object.

tdmPreGroupLevels

Group the levels of factor variable in dset[,colname].

Sensitivity Report Helper Function

Read data accoroding to opts settings.

tdmReadAndSplit

Read and split the task data.

tdmReadTaskData

Read task data.

tdmPreSFA.train

SFA (Slow Feature Analysis) for numeric columns in a data frame.

Function called by SPOT 2.0 tuner

Core regression function of TDMR.

tdmRegressSummary

Print summary output for result from tdmRegressLoop and add result$y.