[PDF] Top 20 Self-organizin map clustering method for the analysis of e-learning activities
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Self-organizin map clustering method for the analysis of e-learning activities
... face-to-face learning system in which the learning activities take place via direct physical contact, the e-learning system supplements and eases the activities of ... See full document
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Multistrategy self-organizing map learning for classification problems
... multistrategy learning of PSO-SOM approach was first introduced by Shi and Eberhart [8] with modified particle swarm ...better clustering of gene datasets. The authors used SOM learning and PSO to ... See full document
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SOMSN: An Effective Self Organizing Map for Clustering of Social Networks
... network analysis has become one of the favorite topics in data ...network analysis is to identify communities in the network. Clustering is an important task for detection of community in ...of ... See full document
6
Analysis Clustering Techniques in Biological Data with R
... Self-Organizing Maps (SOM) formulated by Prof. T Kohonen in1980s Self-organizing Maps (SOM) belongs to the family of neural network based on Competitive ...unsupervised learning process. It is ... See full document
6
An Application of Partitive Clustering Algorithm for Landslide Hazard Zonation
... [9][10], self-organizing map [12] and artificial neural network models ...Kohonen self-organizing maps (SOM) as part of the unsupervised learning algorithm of ANN has been applied as a ... See full document
6
Combining a self organising map with memory based learning
... For small context sizes, LSOMMBL and MBL give the same performance. As the window size increases, LSOMMBL falls behind MBL. The worst drop in performance is just over 1.0% on the fscores (and just over 0.5% on chunk tag ... See full document
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DEM-based analysis of morphometric features in humid and hyper-arid environments using artificial neural network
... a Self Organizing Map (SOM) as a semi-automatic method for analysis and identification of morphometric features in two completely different environments, the Man and Biosphere Reserve “Eastern ... See full document
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Semi-supervised consensus clustering for gene expression data analysis
... final clustering. The consensus clustering algorithms differ in chosen algo- rithms for basic clustering, consensus function and final ...hierarchical clustering(HC) or self-organizing ... See full document
13
A Parallel Clustering Method Study Based on MapReduce
... machine learning, statistics and database ...data analysis model of the information retrieval ...iterative Map and Reduce tasks, which is required in many data mining ... See full document
8
Clustering Web Usage Data using Concept Hierarchy and Self Organizing Map
... Various data mining methods have been have been used to generate models of usage patterns. Models based on association rules, clustering algorithms, sequential analysis and Markov models have been used for ... See full document
7
SELF ORGANIZING MAP BASED CLUSTERING MODEL BY ANALYZING EIGEN SYSTEM OF PCA
... in clustering of the SOM ...means clustering algorithm,other clustering techniques can be used to cluster eigenvalues and eigenvectors of the covariance matrix and also to produce final clusters from ... See full document
8
Mixed Data Clustering Using Dynamic Growing Hierarchical Self Organizing Map With Improved LM Learning
... The main reason for using DGHSOM is that the prototypes formed by DGHSOM preserve both topology and density. This density preservation attribute must be used. As the density matching property of DGHSOM, if a specific ... See full document
7
Exploratory data analysis and clustering of multivariate spatial hydrogeological data by means of GEO3DSOM, a variant of Kohonen's Self Organizing Map
... both analysis are depicted in ...the self-organizing map is carried out in such a way that units with similar weight vectors have similar colors, using a naive contraction model based on the U-matrix ... See full document
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Student behavior analysis using self organizing map clustering technique
... To date, SOM has been widely used in various areas such as tumor classification [28], motor rotor fault detection [29], industry, finance, natural sciences, linguistics, massive textual database [30] and bioinformatics ... See full document
9
Study on K-Means Clustering using MapR in Hadoop
... K-Means Algorithm : The K-Means algorithm is among the few most popular clustering algorithms, and was developed by J. MacQueen in 1967. It’s a distance-based algorithm. It‘s a flat-type (or partitioning) ... See full document
6
Seeking the best blend for deep learning in a flipped classroom – viewing student perceptions through the Community of Inquiry lens
... on self-reported data to help ex- plore how students learned in an ...innovative learning tasks (Anderson & Shattuck, 2012; Herrington & Reeves, ... See full document
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Application of Data Mining in predicting a Course for a Student Based on Previous Records, Financial Status and Personality Traits
... interests, activities in which they participate, ...K-means clustering algorithm in order to group the students into various categories based on their current academic trends and other records from the ... See full document
5
Validity of a method for the self-screening of cardiovascular risk
... by self-screening or vice ...by self-screening with ...by self-screening, with ...the self-screening method were ...The self-screening method for assessing cardiovascular ... See full document
12
The Evidence for The Effectiveness of Active Learning
... information longer and perhaps develop enhanced critical thinking and problem-solving skills, especially if PBL is coupled with explicit instruction in these skills. Teaching cannot be reduced to formulaic methods and ... See full document
5
Online Self Tuning PID Control Using Neural Network for Tracking Control of a Pneumatic Cylinder Using Pulse Width Modulation Piloted Digital Valves
... pneumatic position control using online self-tuning PID controller with a neural network (denoted as STNPID controller) using back propagation scheme. The actuator under control is a vertical double-acting ... See full document
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