• Yagyanath Rimal

This article discusses clearly reviewing the best way to imbalance data management analysis using R. programming, although there is a big difference between machine learning algorithms, algorithms tend to shake in front of data sets that the unbalanced classification misleading predictions and misleading precisions of the research data in the research project. Its main purpose is to explain the research data sampling method handling unbalance commissioner using the R software, whose results have been sufficiently explained with different intermediate results and graphical interpretation to accurately predict the categorical data prediction. Therefore, this paper presents the simplest way to summarize, when data sets with a large unbalanced force categorical and for the analysis of programming data in R.

Multilevel imbalance, upscaling, down sampling, Random Forest, Cost-sensitive

"A BEST WAY OF MULTI-LEVEL IMBALANCE RESEARCH DATA HANDLING USING R PROGRAMMING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.91-96, May-2019, Available :http://www.jetir.org/papers/JETIRBW06018.pdf

"A BEST WAY OF MULTI-LEVEL IMBALANCE RESEARCH DATA HANDLING USING R PROGRAMMING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp91-96, May-2019, Available at : http://www.jetir.org/papers/JETIRBW06018.pdf