This research presents a method to select an ideal feature subset of original and transformed features. The feature selection method utilizes a genetic wrapper scheme that employs classification accuracy as its fitness function. The feature subset generated by the proposed approach usually contains features produced by different transformation schemes. The selection of transformed features prov...

ten by one who has a thorough knowledge of the subject. Far too little attention is paid in most of the Indian colleges and schools to the subject of physical fitness, and it is only by books of this kind that interest in the subject can be aroused. Almost every word of the book is just as applicable to Indian conditions as to European. The information contained in it should be found in every t...

In the typical genetic algorithm experiment, the fitness function is constructed to be independent of the contents of the population to provide a consistent objective measure. Such objectivity entails significant knowledge about the environment which suggests either the problem has previously been solved or other non-evolutionary techniques may be more efficient. Furthermore, for many complex t...

 The meaning of “Quality” is closely allied to cost and customer needs. “Quality” may simply be defined as fitness for purpose at lowest cost.  The component is said to possess good quality, if it works well in the equipment for which it is meant. Quality is thus defined as fitness for purpose.  Quality is the ‘totality of features and characteristics’ both for the products and services that...

Previous approaches to Common Practice Period style automated composition – such as Markov models and Context-Free Grammars (CFGs) – do not well characterise global, context-sensitive structure of musical tension and release. Using local musical expectation violation as a measure of tension, we show how global tension structure may be extracted from a source composition and used in a fitness fu...

Feature selection is an important pre-processing step in mining and learning. A good set of features can not only improve the accuracy of classification, but also reduce the time to derive rules. It is executed especially when the amount of attributes in a given training data is very large. In this paper, an attribute clustering method based on genetic algorithms is proposed for feature selecti...

Deceptivity and epistasis both contribute to make fitness functions hard to optimize for a genetic algorithm. In this note we examine the relation between these concepts, with particular emphasis on their mutual reinforcement.

When attempting to evolve models of the real world through the information obtained by interacting with it, we always come across the same problem: the fitness function for the problem, that is, the real world, can only be known in a sampled manner. In this article we study the effect of different parameters and algorithmic strategies when working with sampled fitness functions in evolutionary ...

The effect of ranking and binary tournament selection on the distribution of fitnesses and genetic correlation is calculated for a finite population. The results are different for continuous and discrete fitness functions. Results for both situations are obtained. These exact results are compared to a previously obtained approximation up to the third cumulant and shown to be in good agreement. ...

There is empirical evidence from a range of disciplines that as the connectivity of a network increases, we observe an increase in the average fitness of the system. But at the same time, there is an increase in the proportion of failure/extinction events which are extremely large. The probability of observing an extreme event remains very low, but it is markedly higher than in the system with ...