TITLE:
Disparity in Intelligent Classification of Data Sets Due to Dominant Pattern Effect (DPE)
AUTHORS:
Mahmoud Zaki Iskandarani
KEYWORDS:
Pattern Recognition, Neural Networks, Ranking, Datasets, Weight Elimination, Pruning, Mutation, Genetic Algorithms
JOURNAL NAME:
Journal of Intelligent Learning Systems and Applications,
Vol.7 No.3,
July
10,
2015
ABSTRACT: A hypothesis of the existence of dominant
pattern that may affect the performance of a neural based pattern recognition
system and its operation in terms of correct and accurate classification,
pruning and optimization is assumed, presented, tested and proved to be
correct. Two sets of data subjected to the same ranking process using four main
features are used to train a neural network engine separately and jointly. Data
transformation and statistical pre-processing are carried out on the datasets
before inserting them into the specifically designed multi-layer neural network
employing Weight Elimination Algorithm with Back Propagation (WEA-BP). The
dynamics of classification and weight elimination process is correlated and used
to prove the dominance of one dataset. The presented results proved that one
dataset acted aggressively towards the system and displaced the first dataset
making its classification almost impossible. Such modulation to the
relationships among the selected features of the affected dataset resulted in a
mutated pattern and subsequent re-arrangement in the data set ranking of its
members.