clustering-and-selection algorithm
A Secure Multi-Keyword Search Based On Ranking Using Selection Algorithm in Clustering
... ABSTRACT:The advent of distributed systems, data owners are motivated to outsource their complex data management systems from local sites to commercial public cloud for great flexibility and economic savings. But for ...
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IMPLEMENTATION OF CLUSTERING-BASED FEATURE SUBSET SELECTION ALGORITHM-FAST
... Feature selection involves recognizing a subset of maximum of helpful features that produces attuned results as the unique set of ...FAST algorithm can be implemented from mutually efficiency and ...
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CLUSTERING-BASED FEATURE SUBSET SELECTION ALGORITHM USING FAST
... Feature selection involves identifying a subset of the most useful features that produces compatible results as the original entire set of ...feature selection algorithm may be evaluated from both ...
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E}nergy Efficient Homogenous Clustering and Cluster Head Selection Algorithm for {WSN
... homogeneous clustering and cluster head selection algorithm for wireless sensor network that saves power and prolongs network ...homogeneous algorithm makes sure that every node is either a ...
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A FAST CLUSTERING-BASED FEATURE SUBSET SELECTION ALGORITHM
... Feature selection involves identifying a subset of the most useful features that produces compatible results as the original entire set of ...feature selection algorithm is basically evaluated from ...
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A Review Of Fast Clustering-Based Feature Subset Selection Algorithm
... crossover, selection and inheritance to select a feature ...classification algorithm often results in better classification accuracy of the selected subsets than the accuracy achieved with filter methods ...
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FAST Clustering Based Feature Subset Selection Algorithm for High Dimensional Data
... Feature selection is the process of selecting a subset of relevant features for use in model ...feature selection technique is that the data contains many redundant or irrelevant ...Feature selection ...
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Collaborative Clustering Selection Algorithm Based on T LEACH
... T-LEACH algorithm saves a lot of total energy consumption at the same time compared with the traditional LEACH, so that the entire network can extend the life cycle because of the improved ...T-LEACH ...
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Feature Selection Algorithm Using Fast Clustering and Correlation Measure
... Feature selection algorithms which exist are Wrapper, Relief, filter, embedded ...learning algorithm are used for feature ...feature selection and learning ...
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Survey on Feature Subset Selection Algorithm in Brain Interaction Patterns
... feature selection and clustering is a complicated process in interaction patterns of brain ...and clustering techniques used in ...Ranking algorithm was used to select the best cluster for ...
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ABSRACT : Feature selection is a process which selects the subset of attributes from the original dataset by
... data. Clustering based feature selection algorithm remove the redundancy from the attributes and also provide the reduced or required attributes from the original attribute ...set. Clustering ...
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A New Integrated Fuzzifier Evaluation and Selection (NIFEs) Algorithm for Fuzzy Clustering
... higher clustering accuracy, which few studies have ...and selection algorithm and tested it using real ...fuzzy clustering, and the best clustering accuracy was achieved for tested ...
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OUTLIER DETECTION FOR DYNAMIC DATA STREAMS USING WEIGHTED K-MEANS
... k-means clustering the data items are grouped together by predetermining the k value, so if the k-value is taken as very high there may be inconsistency in data and if the value is too low some useful data may be ...
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Clustering of the Values of a Response Variable and Simultaneous Covariate Selection Using a Stepwise Algorithm
... When analyzing real-life data, the practitioner will have to fix the number r of clusters. An automated procedure to find the optimal number of clusters would be helpful. As a first attempt, one could simply vary r over ...
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International Journal of Computer Science and Mobile Computing
... Lloyd’s algorithm [1], which initially chooses k centers ...Lloyd’s algorithm is unknown. This algorithm may converge to a local minimum with an arbitrarily bad distortion with respect to optimal ...
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The Family of LEACH –Review
... It considers the residual energy as the main criteria for CH selection. In LEACH, the CH selection is based on the probabilistic method and in the first round. Every node has the equal chance to become the ...
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International Journal of Computer Science and Mobile Computing
... many algorithm available and it support for the data mining task like pre-processing, classification, feature selection and clustering here we choose the above Weather dataset and apply the decision ...
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Clustering Network Topology Control Method Based on Responsibility Transmission
... CABRT algorithm and LEACH algorithm (Figure ...LEACH algorithm and basic CNT- CABRT algorithm ...CNTCABRT algorithm decreased more slowly than that of the LEACH ...LEACH ...
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A Methodology for Incorporation of Domain Ontology in Knowledge Discovery Process for Interpretation and Improvement of Mining Results
... The clustering is done such that (i) there is high similarity between the objects of same cluster (high intra cluster similarity) and (ii) low inter-cluster ...a clustering algorithm which can be ...
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Application of Data Mining in predicting a Course for a Student Based on Previous Records, Financial Status and Personality Traits
... Clustering aims to partition n observations into k clusters. Each observation belongs to the cluster with the nearest mean. The following Figure 1 shows the implementation of K-means clustering using GMDH ...
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