[PDF] Top 20 A Cluster Feature-Based Incremental Clustering Approach to Mixed Data
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A Cluster Feature-Based Incremental Clustering Approach to Mixed Data
... is to develop an incremental clustering algorithm that can handle numerical as well as categorical attributes in a given ...a cluster feature-based algorithm, CFICA that can ... See full document
6
A Novel K-Means Based Clustering Algorithm for High Dimensional Data Sets
... a data set is too large to be stored in the main memory, it is possible to divide the data into different subsets that can fit the main memory and to use the selected cluster ... See full document
5
Data-Collection using Clustering Approach in Wireless Sensor Network Design based on Heuristic Algorithms
... due to infeasibility of in-person attendance in data collection and the remoteness of areas of ...the data collected by them to the designated sensors which are called as cluster heads ... See full document
7
Spatio-temporal data mining in palaeogeographic data with a density-based clustering algorithm
... objects. Clustering on a sample of a given large data set may lead to biased ...scalable clustering algorithms are needed [HAN & KAMBER, ...showed to work well on datasets of ... See full document
103
A NOVEL KERNEL BASED FUZZY C MEANS CLUSTERING WITH CLUSTER VALIDITY MEASURES
... fuzzy clustering is corrected, and a kernel fuzzy c-means clustering-based fuzzy SVM algorithm (KFCM-FSVM) is developed by Yang et al (2011) to deal with the classification problems with ... See full document
9
A divide-and-conquer strategy using feature relevance and expert knowledge for enhancing a data mining approach to bank telemarketing
... devoted to DM algorithm design, a smaller number emphasizes the need to divide the problem to reduce the feature selection search ...on feature space ...the feature selection ... See full document
31
Fuzzy approach to discrete data reduction: an application in economics for assessing the skill premium
... used to reproduce most of the variability present in the original dataset (Ghodsi ...the data to be vec- tors of a real ...justification to support this ...of cluster analysis for ... See full document
16
AN EFFICIENT APPROACH TO IMPROVE ARABIC DOCUMENTS CLUSTERING BASED ON A NEW KEYPHRASES EXTRACTION ALGORITHM
... a data structure that allows efficient string matching and ...applied to fundamental string problems such as finding the longest repeated substring, strings comparisons , and text ...as clustering ... See full document
14
Clustering Approach to Stock Market Prediction
... stock clustering analysis framework is automated classification using k-means ...2000) to achieve our ...stocks to k different groups represented by the ...perhaps to choose the ‘right’ k ... See full document
11
Document Clustering Approach Using Internal Criterion Function
... other data, are written as unstructured free- text reports or ...difficult to standardize and thus difficult to mine, even specialists from the same discipline cannot agree on unambiguous terms ... See full document
9
A CLUSTERING-BASED APPROACH FOR EVALUATION OF EO IMAGE INDEXING
... the feature space, built by the feature descriptors extracted from EO images, by internal evaluation of clustering performed on the ...of clustering allows computers to find the ... See full document
6
Fatigue Feature Extraction Analysis based on a K-Means Clustering Approach
... on clustering analysis using a K-means approach for fatigue feature dataset ...is to group the dataset as closely as possible (homogeneity) for the scattered ...input data for the ... See full document
8
AN IMPROVED TEACHING-LEARNING BASED OPTIMIZATION APPROACH FOR FUZZY CLUSTERING
... Step 1: objective function; define the optimization problem as minimizing overall deviation of a partitioning or maximize compactness inside the clusters. This is simply computed as the overall summed distances between ... See full document
8
Incremental k-means clustering algorithms: a review
... Abstract: Clustering is the process of grouping the object based on their attributes and features such that the data objects that are similar or closer to each other are put in the same ... See full document
5
Semantic Based Cluster Content Discovery in Description First Clustering Algorithm
... the data. Clustering of the data is an approach that is used to group the similar ...Tree Clustering) were initiated to use the concept of phrases to find the ... See full document
6
Urdu to Punjabi Machine Translation: An Incremental Training Approach
... frequent. To resolving the word segmentation problem in Urdu is quite a challenging task and need a full-fledged algorithm for ...related to alphanumeric ...developed to handle these types of ... See full document
12
A Survey Paper on Crime Prediction Technique Using Data Mining
... Model Based on Bayesian Learning ...related to geographic ...Journey to Crime, create a geographic profile which is a probability distribution of being the next crime site on known geographical ... See full document
5
Behind the boardroom's door: the role and contribution of corporate boards
... connections to the firm’s performance, that relationship is critical to the sustainable future of the ...striving to attain meaningful consensus on board and enterprise wide issues, is fundamental ... See full document
14
Differential anti-glycan antibody responses in Schistosoma mansoni-infected children and adults studied by shotgun glycan microarray.
... antibodies to only a small set of schistosome-related glycans have been determined in a limited number of studies ...antibodies to immunity to schistosomes may be overcome using a shotgun glycan ... See full document
10
An optimization-based wrapper approach for utility-based data mining
... impossible to encounter the optimal stage without diversity across the ...possible to reach the optimal ...due to a combination of factors: low population size, aggressive fitness function, and flat ... See full document
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