Only One Neuron either N-bit Parity Rule Based Modified Translated Multiplicative or McCulloch-Pitts Models for Some Machine Learning Problems

Year 2016, , 67 - 72, 26.12.2016

Ali Özdemir Mehmet Melih İnal

https://doi.org/10.18201/ijisae.267039

Cited By: 1

Abstract

In this
study, solutions to machine learning problems such as Monk’s 2 (M₂),
Balloon and Tic-Tac-Toe problems employing a single neuron dependent on rules
which use either modified translated multiplicative (π_m) neuron or
McCulloch-Pitts neuron model is proposed. Since M₂ problem is
similar to N-bit parity problem, translated multiplicative (π_t)
neuron model is modified for M₂ problem. Also, McCulloch-Pitts
neuron model is used to increase classification performance. Then either πm or
McCulloch-Pitts neuron model is applied to Balloon and Tic-Tac-Toe problems.
When the result of proposed only one π_m neuron model that is not
required any training stage and hidden layer is compared with the other
approaches, it shows satisfactory performance.

Keywords

Machine learning, Modified translated multiplicative neuron model, Monk’s and Balloon problems, N-bit parity problem, Translated multiplicative neuron model

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