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What is Effective Input Partitioning for ALM about?

This document discusses a new algorithm for partitioning the input domain for implementing the Active Learning Method (ALM) algorithm. ALM is a pattern-based soft computing algorithm that uses Ink Drop Spread (IDS) for feature extraction. The proposed algorithm partitions the input domain with few computations, making it suitable for real-time applications. Previous partitioning algorithms had high computational costs. The proposed algorithm is evaluated on system modeling and pattern recognition applicatio

Author

m1.nourian

Language

EN