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DMTL

DMTL is an R package for applying distribution mapping based transfer learning. DMTL employs the widely renowned concept of histogram matching and extend it to include distribution estimates like kernel density estimates. The typical use case would be if somebody wants to utilize data from multiple sources for similar kind of experiments in statistical modeling but there exists significant distribution shift between both predictors and response values. In this case, DMTL can alleviate this shift by generating a distribution matching based map and transfer the target data to the source domain to utilize the available source data for modeling using various predictive modeling techniques.

Note: The package is currently waiting evaluation from the CRAN submission team.

In the meanwhile- if you want to install it on your local machine, you will need the devtools package which is available in CRAN. You can install it using the following command -

	install.packages("devtools")

Once you have it, you need to use the following code chunk -

	library(devtools)  
	install_github("dhruba018/DMTL")  

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Version

Install

install.packages('DMTL')

Monthly Downloads

202

Version

0.1.2

License

GPL-3

Issues

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Maintainer

Saugato Rahman Dhruba

Last Published

February 18th, 2021

Functions in DMTL (0.1.2)

dist_match

Distribution Matching for Source and Reference Datasets
DMTL

Distribution Mapping based Transfer Learning
EN_predict

Predictive Modeling using Elastic Net
RF_predict

Predictive Modeling using Random Forest Regression
SVM_predict

Predictive Modeling using Support Vector Machine
match_func

Estimate Inverse Mapping
performance

Evaluate Regression Model Performance using Various Metrics
estimate_cdf

Estimate Cumulative Distribution
zscore

Standardize matrix per column
norm_data

Normalize matrix per column in [0, 1]
norm01

Normalize vector in [0, 1]
confined

Restrict data in a given interval