EFFICIENT DECISION TREE BASED PRIVACY PRESERVING APPROACH FOR UNREALIZED DATA SETS
S. Nithya, P. Senthil Vadivu · 2013
Privacy preserving data mining (PPDM) is major issue in the areas of datamining and security. PPDM datamining algorithms are analysis the results of impact data privacy. Objective of PPDM is to preserve confidential information by applying datamining tasks without modifying the original data. Because privacy preservation is important for datamining and machine learning applications, it measures to measures designed to protect private information. Numerous datamining techniques are analysis the result of preserved data. But still it becomes loss of information and reduces the utility of training samples. In this research we introduce a decision tree based privacy preserving approach. In this approach the original dataset or data samples are converted into the unrealized dataset where