[PDF] Top 20 A Novel Kernel Clustering Algorithm
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A Novel Kernel Clustering Algorithm
... new novel kernel-clustering algorithm that is robust and converges to the global ...proposed kernel algorithm performs better than the standard kernel K-means ... See full document
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A Novel Clustering Algorithm Using K means (CUK)
... a novel algorithm of clustering using K-means ...proposed algorithm uses K-means to cluster data objects by using one additional centroid, several partionining and merging process are ... See full document
6
A Novel Direct Relational Heuristic Algorithm of Possibilistic Clustering
... The paper deals with the problem of a heuristic approach to possibilistic clustering. The approach is based on the concept of allotment among fuzzy clusters. The paper provides the description of basic definitions ... See full document
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A Novel Spatial Clustering Algorithm Based on Delaunay Triangulation
... spatial clustering algorithm named NSCABDT (Novel Spatial Clustering Algorithm Based on Delaunay ...all clustering operations are performed on the graph infor- ... See full document
9
A Divisive Information Theoretic Feature Clustering Algorithm for Text Classification (Kernel Machines Section)
... Divisive Clustering obtains better results than Information Gain at all number of ...By clustering words we obtain more robust estimates of word class probabilities which lead to higher classification ... See full document
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Hybrid Genetic Algorithm with K Means for Clustering Problems
... A novel approach of cluster based optimal ranking of clicked URLs using genetic algorithm for effective personalized web search [12], Optimal clustering of microgrids based on droop controller for ... See full document
14
Clustering Sentence-Level Text via a Novel Nebulous Relational Clustering Algorithm
... PageRank algorithm is that the importance of a node within a graph can be determined by taking into account global information recursively computed from the entire graph, with connections to high-scoring nodes ... See full document
7
Polynomial Kernel Function based Support Vectors for Data Stream Clustering
... vector clustering (SVC) is an important clustering algorithm based on support vector machine (SVM) and kernel ...SVC algorithm performed better than the other traditional ... See full document
7
A Survey of Clustering Algorithm for Very Large Datasets
... a novel hierarchical clustering algorithm that acts in between the centroid-based and the all-point ...CURE algorithm is more robust to outliers, and identifies clusters having non-spherical ... See full document
8
Segmentation of Medical Images using Adaptively Regularized Kernel based Fuzzy C Means Clustering
... proposed algorithm on the publicly available brain tumor image segmentation (BRATS) MRI benchmark by comparing the center of the cluster that overlaps with the tumor, with the center of the tumor in the ... See full document
6
A Novel Feature Clustering Algorithm for Evaluation of Descriptive Type Examination
... Every descriptive answer is evaluated manually because there is no proper alternative for manual evaluation. The volume of evaluation increased a lot and become difficulty to handle all the corrections in a manual way. ... See full document
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Firefly Algorithm Solution to Improving Threshold Distributed Energy Efficient Clustering Algorithm for Heterogeneous Wireless Sensor Networks
... a novel approach called ITDEEC (Improving Threshold Distribution Energy Efficient Clustering Algorithm for heterogeneous WSN) based on elimination of the nearest nodes to the base station in the ... See full document
9
Prediction of protein secondary structures with a novel kernel density estimation based classifier
... In the experiments reported in this article, the 4 parame- ters in the RVKDE algorithm were set as m = 1, β = 3, k = 38, and k' = 60, through a validation process. The valida- tion dataset was derived from the ... See full document
6
Mining Dynamic Communities based on a Novel Link-Clustering Algorithm
... detection algorithm called link-clustering which uses link-based clustering paradigm intertwined with a novel representative-based algorithm to handle these ...The algorithm ... See full document
8
A Survey on Techniques used for Sentence Clustering of Text Documents
... a novel fuzzy relational clustering ...PageRank algorithm to each cluster, and interpreting the Page-Rank score of an object within some cluster as a likelihood, the Expectation- Maximization (EM) ... See full document
8
A Novel Approach Towards K-Mean Clustering Algorithm With PSO
... K-Means is one of the simplest unsupervised learning algorithms that solve the well-known clustering problem because of its fast execution and easy implementation [24]. To classify a given data set into a fixed ... See full document
9
Semi-supervised Feature Extraction Method Using Partial Least Squares and Gaussian Mixture Model
... a kernel for modified Partial Least Squares method with a Gaussian Mixture Model (GMM) (see [2], [15]) clustering ...supervised kernel exploits the information conveyed by the labeled samples and the ... See full document
5
Evaluating the performance of various hybrid fuzzy clustering algorithms on brain magnetic resonance images
... C-means algorithm, for brain MR ...refinement clustering algorithms such as ...multiple kernel Fuzzy C means clustering algorithm produces a segmented image more promising than do the ... See full document
10
An Overview of Semi-Supervised Fuzzy Clustering Algorithms
... fuzzy clustering algorithm using Kernel methods with the combination of learning labeled and unlabeled data to obtain best ...this algorithm is to use function to map data elements in the ... See full document
6
An intelligent system based on kernel methods for crop yield prediction
... a clustering algorithm to cluster time series associated with points on the land, we obtain clusters that represent land regions with relatively homogeneous ... See full document
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