Article History: Received: 17/03/2015 Accepted: 17/02/2016 Published:26/5/2016 This study optimises manually derived rule-based expert system classification of objects according to changes in their properties over time. One of the key challenges that this study tries to address is how to classify objects that exhibit changes in their behaviour over time, for example how to classify companies’ s...

In this paper we use “Clustering Method” to understand whether stock market volatility can be predicted at all, and if so, when it can be predicted. The exercise has been performed for the Indian stock market on daily data for two years. For our analysis we map number of clusters against number of variables. We then test for efficiency of clustering. Our contention is that, given a fixed number...

C R E D IT S ( T O P T O B O T T O M ): C A S E Y D U N N ; R E IN H A R D T M Ø B J E R G K R IS T E N S E N ; C H R IS T IN A H O L Z A P F E L A N D W IL L IA M B R A D S H A W among organisms, identifying differences within equivalent pieces of DNA in various species. Controversy often ensued when those early results didn’t agree with more traditional classifi cation schemes, such as those ...

1. Introduction Relevance logic has become ontologically fertile. No longer is the idea of relevance restricted in its application to purely logical relations among propositions, for as Dunn has shown in his (1987), it is possible to extend the idea in such a way that we can distinguish also between relevant and irrelevant predications, as for example between " Reagan is tall " and " Reagan is ...

DUNN and Charles (1937, p. 14) opens with an understated assessment on the state of developmental genetics at the time: “The processes which lead to the formation of patterns during ontogeny in animals are at present very imperfectly understood.” This was the first in a series of five articles that proposed that understanding the highly variable coat patterns of the mouse could provide a model ...

Internal cluster validity measures (such as the Calinski-Harabasz, Dunn, or Davies-Bouldin indices) are frequently used for selecting appropriate number of partitions a dataset should be split into. In this paper we consider what happens if treat such indices objective functions in unsupervised learning activities. Is optimal grouping with regards to, say, Silhouette index really meaningful? It...