Creating classification rules using grammatical evolution

Credit Classification Using Grammatical Evolution

Grammatical Evolution (GE) is a novel data driven, model induction tool, inspired by the biological geneto-protein mapping process. This study provides an introduction to GE, and demonstrates the methodology by applying it to model the corporate bond-issuer credit rating process, using information drawn from the financial statements of bond-issuing firms. Financial data and the associated Stand...

Evolving Phonological Rules Using Grammatical Evolution

Phonetic transcription is a core procedure of continuous speech recognition systems and speech synthesizers. The more correct phonetic translation is the more successful applications using phonetic transcription are. Phonological rules translate text to graphemes. These rules significantly reduce size of databases with words and it’s phonetic transcription and speeds up transcription process. T...

Evolving Market Index Trading Rules Using Grammatical Evolution

Solving Classification and Curve Fitting Problems Using Grammatical Evolution

Grammatical Evolution is related to the idea of genetic programming in that the objective is to find an executable program or function. GE offers a solution by evolving solutions according to a user specified grammar (BackusNaur Form). In this paper GE is used to construct a classifier for some well known datasets. and curve fitting problems without the need to assume the equation shape.

Grammatical Evolution Rules: The Mod and the Bucket Rule

We present an alternative mapping function called the Bucket Rule, for Grammatical Evolution, that improves upon the standard modulo rule. Grammatical Evolution is applied to a set of standard Genetic Algorithm problem domains using two alternative grammars. Applying GE to GA problems allows us to focus on a simple grammar whose effects are easily analysable. It will be shown that by using the ...