• Dr. R. Rajani
• B. Phani Krishna
• Sk.Fareeda
• A.E. Kokila

Predicting human behavioral data is challenging due to its characteristics like huge in size of data, different behaviors and interest outcomes of every individual is imbalance in state. Due to this, predicting an accurate model for identifying the behavior of human beings is a biggest challenge. To address this challenge we can depend upon various statistical models to describe about the behavioral data of individuals. Here, we consider an algorithm ID3 (Iterative Dichotomiser 3) Decision Tree which is a variant of decision tree algorithms. It is the most suited algorithm for identifying the categorical data values.

categorical data values, Human behavioral data, Feature selection

"Predicting behavioral data using ID3", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.226-228, May 2019, Available :http://www.jetir.org/papers/JETIRCU06047.pdf

"Predicting behavioral data using ID3", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp226-228, May 2019, Available at : http://www.jetir.org/papers/JETIRCU06047.pdf