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Due to heavy use of electronics devices nowadays most of the information is available in electronic format and a substantial portion of information is stored as text such as in news articles, technical papers, books, digital libraries, email messages, blogs, and web pages. Mining the knowledge like pattern finding or clustering of similar kind of words is(More)
In this paper, a new technique for facial expression recognition is proposed which uses the statistical feature of the whole face and classify the expression using neural network classifier. When the face image is input, region of interest (ROI) is being obtained to evaluate the statistical feature of the face. Using these, features we classify the face(More)
Feature extraction and feature normalization is an important preprocessing technique, usually employed before classification. Feature normalization is a useful step to restrict the values of all features within predetermined ranges. However, appropriate choice of normalization technique and normalization range is an important issue, since, applying(More)
Mining the knowledge from climate data is one of the important issues due the rapid development and the extensive use of data acquisition technology. Earth science data increases tremendously, it is containing a large amount of information and knowledge. In this paper we used earth science data which is downloaded from the NASA website. The Earth science(More)
The contiguous sequences of the terms (N-grams) in the documents are symmetrically distributed among different classes. The symmetrical distribution of the N-Grams raises uncertainty in the belongings of the N-Grams towards the class. In this paper, we focused on the selection of most discriminating N-Grams by reducing the effects of symmetrical(More)
Association rule mining is one of the important problems of data mining. Single minimum support based approaches of association rule mining suffers from "rare item problem". An improved approach MSApriori uses multiple supports to generate association rules that consider rare item sets. Necessity to first identify the "large" set of items contained in the(More)
The selection of most informative terms reduces the feature set and speed up the classification process. The most informative terms are highly affected by the correlative association of the terms. The rare terms are most informative than sparse and common terms. The main objective of this study is assigning a higher weight to the rare terms and less weight(More)