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This paper presents a hybrid filter–wrapper feature subset selection algorithm based on particle swarm optimization (PSO) for support vector machine (SVM) classification. The filter model is based on the mutual information and is a composite measure of feature relevance and redundancy with respect to the feature subset selected. The wrapper model is a(More)
Clustering is an unsupervised approach to extract hidden patterns from the datasets. There are certain challenges in clustering, though it is very much difficult to produce good clustering, researchers have provided the solutions through various hybrid approaches. The proposed work is based on enhancing the clustering results by using two algorithms: First(More)
Large amounts of databases are created daily in data storage Due to this it becomes very difficult to retrieve the images require for applications in various fields. Thus Content Based Image Retrieval Techniques play an important character in image processing. Here we will be using various masking methods to find out different features and apply different(More)
During past few decades, researchers worked on data preprocessing techniques for the datasets. Data preprocessing techniques are needed, where the data are prepared for mining. The performance of data mining algorithms in most cases depends on dataset quality, since low-quality training data may lead to the construction of over?tting or fragile classi?ers.(More)
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