[PDF] Top 20 Application of Factor Analysis to k means Clustering Algorithm on Transportation Data
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Application of Factor Analysis to k means Clustering Algorithm on Transportation Data
... components analysis was used to propose a new algorithm on elderly people-disability ...based k-means algorithm on various UCI datasets and showed that it performs better compared to ... See full document
7
Medical Image Segmentation using Modified K Means Clustering
... image analysis problems require a segmentation stage in order to detect objects or divide the image into regions which can be considered homogeneous according to a given criterion, such as colour, motion, texture, ... See full document
5
Implementing & Improvisation of K-means Clustering Algorithm
... many clustering techniques proposed but K-means is one of the oldest and most popular clustering ...to analysis and then the selection of the initial centroids will be made randomly and ... See full document
13
Performance of Students Evaluation in Education Sector Using Clustering K-Means Algorithms
... unknown data, various methods and techniques were used such as the Association rules, pattern mining, classification technique, clustering technique, prediction, Supervised and unsupervised learning ... See full document
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Online Full Text
... Sekhon J.S., et al. [12] bring up the factor that effected to accuracy and efficiency of clustering algorithm is dependent on the input data. The removing unimportant features from the dataset ... See full document
6
Performance Evaluation of K means Clustering Algorithm with Various Distance Metrics
... pure clustering or hybrid ...Efficient K-means Clustering Algorithm Using Simple Partitioning presented by Ming-Chuan Hung, Jungpin Wu+, Jin-Hua Chang, In this paper an efficient ... See full document
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Enhanced K-Means Clustering Algorithm Using Collaborative Filtering Approach
... first means used as input and in this case output is final ...last means are the means of clusters, if an algorithm is required to create a cluster then K-means will be the ... See full document
6
Algorithm 1: The k-means clustering algorithm
... scientific data collection has resulted in large scale accumulation of data per- taining to diverse ...huge data banks. Cluster analysis is one of the major data analysis methods ... See full document
5
A Comparative Study on K-Means And Genetic Algorithm For Data Clustering
... bulky data sets jumbled with artificial intelligence, machine learning, statistics and database ...conventional data base ...[2]. Clustering is one of the outstanding data mining algorithms, ... See full document
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Application of Modified K Means Clustering Algorithm in Segmentation of Medical Images of Brain Tumor
... considered. Clustering technique searches for distinct groups in the space allocated for ...of clustering is to separate the data into several number of partitions and the volume is the feature space ... See full document
5
K means Clustering Algorithm Based on E Commerce Big Data
... simple k-means clustering algorithm with an appropriate ...the k-means clustering ...the clustering algorithm and we have used Euclidean distance for ... See full document
5
Iteration Reduction K Means Clustering Algorithm
... involves analysis of data from different perspectives and summarizes it into valuable ...in data mining is Clustering. In cluster analysis, a set of objects are grouped based on the ... See full document
6
Application of Grid-based K-means Clustering Algorithm for Optimal Image Processing
... existing K-means clustering algorithm, one needs to predefine the number of clusters ...of clustering validity indices in a given dataset [14], ...the clustering validity index ... See full document
18
Clustering for binary data sets by using genetic algorithm incremental K means
... of data that were collected by individuals, organizations or either firms has triggered the initiative to process and analyse this type of ...discriminant analysis, multi-dimensional scaling, ... See full document
6
An Efficient Global K-means Clustering Algorithm
... GKM algorithm reduced its heavy computational ...EGKM algorithm is that it can reduce the computation load ...fourteen data sets from UCI machine repository show that our variations of the GKM ... See full document
9
Hybrid optimization for k-means clustering learning enhancement
... K-means clustering, originating from signal processing is a method of vector quantization (Al-Jarrah et ...cluster analysis in data mining. The aim of K-means ... See full document
47
Clustering Behavioral Data for Advertising Purposes using K Prototypes Algorithm
... on clustering and analyzing behavioral ...unsupervised clustering algorithms to identify the consumption patterns of the customers, in order to form specific customer classes containing customers exhibiting ... See full document
6
Big Data Analytics: Map Reduce Function using BIRCH Clustering Algorithm
... Big Data information is represented in unstructured form and NoSQL is used for query ...of data also too large and simple Query processing is not sufficient and ...of data, extracting the ... See full document
8
Clustering in Big Data Using K Means Algorithm Ajitesh Janaswamy
... big data like volume, velocity and variety is the need of ...classic k-means algorithm is ...of algorithm is demonstrated on various real and synthetic ... See full document
6
A REVIEW ON FORENSIC DOCUMENT ANALYSIS USUNG APRIORIALGORITHM
... forensic analysis in integrated surrounding via classification and clustering algorithm, was present in ...an application domain which is related to email were grouped by using structural, ... See full document
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