In this research, a new uncertainty clustering method has been developed and applied to the spatial time series with seasonality. The unsupervised grouping is based on Neighbourhoods Median Seasonal Entropy. This classification aims discover similar behaviours for group find dissimilarity measure concerning reference r. Neighbourhood’s Internal Verification Coefficient criterion makes it possib...

In this work, popular discretization techniques for continuous features in data sets are surveyed, and a new one based on equal width binning and error minimization is introduced. This discretization technique is implemented for the UCI Machine Learning Repository [7] dataset, Adult database and tested on two classifiers from WEKA tool [6], NaiveBayes and J48. Relative performance changes for t...

This study analyzes the effect of discretization on classification of datasets including continuous valued features. Six datasets from UCI which containing continuous valued features are discretized with entropy-based discretization method. The performance improvement between the dataset with original features and the dataset with discretized features is compared with k-nearest neighbors, Naive...

A new identification algorithm for estimation of nonlinear characteristic in Wiener system with FIR linear element under existence of random noise is proposed. The assumptions imposed on unknown characteristic are weak. The algorithm is based on the idea of local median computing. The convergence in probability of the estimate is proved for each continuity point of the unknown characteristic. T...

244 Abstract— Color histogram is one of the common techniques used in image retrieval systems. However, the main problem with color histogram indexing is that it does not take the color spatial distribution into consideration. In this paper, we introduce the local histograms to describe the spatial information of colors, even though, a single local histograms is not enough for efficient and rob...

An effective Content-Based Image Retrieval (CBIR) system is based on efficient feature extraction and accurate retrieval of similar images. Enhanced images by using proper filter methods can also, play an important role in image retrieval in a compressed frequency domain since currently most of the images are represented in the compressed format by using the Discrete Cosine Transformation ( DCT...