ATISA: Adaptive Threshold-based Instance Selection Algorithm
We propose three instance reduction techniques called ATISA1,2,3. ATISA maintain important border and inner points per class based on an adaptive threshold. When compared with the state-of-the-art algorithms, ATISA1 obtains better accuracy rates and promising reduction rates. ATISA is faster than DROP3, ICF and HMN-EI.
instance selection instance-based learning algorithms