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An evidential comprehension and the substantial insights to analyze the clinical data has the maximum level of significance in the clinical decision-making (CDM) process. Many DM researchers have proven clustering methods are efficient, in looking up worthwhile critical information by describing important data classes. Finding optimized structuresof real-complex data is a challenging task. Parallel...
In this elaborated paper, distinguished two approaches required in order to build an unlabelled data by using an automated feature subset feature selection algorithm: the requirement for seeking the number of groups to conjunct with feature selection (fs), the requirement to normalize the inclination of feature selection (fs) procedure regarding measurements. Here, to investigate a component determination...
Mining Frequent Itemsets from a transaction database is an very important and most widely used task for analyzing data in any business. It is the preliminary step to find the correlation between the items which are called Association Rules. Closed Frequent Itemsets are the compact representation of the Frequent Itemsets which can save memory and time for large, dense data. It is very challenging to...
Mining frequent itemsets and association rules on data stream is an important and challenging task. Tree based approaches have been extensively studied and widely used for their parallel processing capability. Itemset Tree is an efficient data structure to represent the transactions for performing selective mining of frequent itemsets and association rules. The transactions are inserted incrementally...
A set function on a ground set of size n is approximately modular if it satisfies every modularity requirement to within an additive error, approximate modularity is the set analog of approximate linearity. In this paper we study how close, in additive error, can approximately modular functions be to truly modular functions. We first obtain a polynomial time algorithm that makes O(n2 log n) queries...
The main focus of this paper is on stabilization of non-linear system using proposed Hybrid Neuro-fuzzy Logic Controller based on Radial Basis Function Network (HNFRBFN). A control unit matrix has been introduced according to the non-linearity and uncertainty of the plant. The parameters used to obtain the individual control action in this matrix are optimized by Gradient Descent Algorithm. IF part...
Consider the problem of laying out a set of images that match a query onto the nodes of a grid. We are given a score for each image, as well as the distribution of patterns by which a user's eye scans the nodes of the grid and we wish to maximize the expected total score of images selected by the user. This is a special case of the \emph{Markov layout} problem, in which we...
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