An Intelligent Learning Machine

Abstract

In this paper we present a new learning system, the Intelligent Learning Machine (ILM). We associate intelligence with the power to learn, forget, grow, contract, interact, and co-operate incrementally, on-line, and in real time. Intelligence in the ILM is based upon the use of a specially customized weight table. The ILM enables parallel data processing and it is well suited to a wide variety of applications and promises unprecedented performance gains in dynamic environments. Here we show how Linear and Non-linear Regression and Classification modeling methods are transformed into intelligent methods. This method has now been successfully software implemented and tested using a variety of databases. Hardware implementation of the ILM is feasible and we foresee an ILM chip for faster computations and mobile applications. Subsequent papers will show how the ILM can be applied to methods such as Bayesian Models, Markov Chain, Hidden Markov Models, Linear Discriminant Analysis, Association Rules, OneR, Principal Component Analysis and Linear Support Vector Machines.