Recommender systems are widely used to cope with the problem of information overload and, consequently, many recommendation methods have been developed. However, no one technique i...
Neural networks have played an important role in intelligent medical diagnoses. This paper presents an Improved Constructive Neural Network Ensemble (ICNNE) approach to three medic...
In this paper, we present PRICES, an efficient algorithm for mining association rules, which first identifies all large itemsets and then generates association rules. Our approach ...
The effort of data mining, especially in relation to association rules in real world business applications, is significantly important. Recently, association rules algorithms have ...
Many time series exhibit dynamics over vastly different time scales. The standard way to capture this behavior is to assume that the slow dynamics are a “trend”, to de-trend t...
Microarray datasets are often too large to visualise due to the high dimensionality. The self-organising map has been found useful to analyse massive complex datasets. It can be us...
We propose a new feature selection criterion not based on calculated measures between attributes, or complex and costly distance calculations. Applying a wrapper to the output of a...
Abstract. Earlier research has resulted in the production of an ‘allrules’ algorithm for data-mining that produces all conjunctive rules of above given confidence and coverage...
Alan P. Reynolds, Graeme Richards, Victor J. Raywa...
Abstract. Image compression methods such as JPEG use quantisation of discrete cosine transform (DCT) coefficients of image blocks to produce lossy compression. During decoding, an...
We present an approach to classification of biomedical terms based on the information acquired automatically from the corpus of relevant literature. The learning phase consists of...