# Comparison the various clustering algorithms of weka tools

@inproceedings{Sharma2012ComparisonTV, title={Comparison the various clustering algorithms of weka tools}, author={Narendra Sharma and Aman Bajpai and Mr. Ratnesh Litoriya}, year={2012} }

Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Weka is a data mining tools. It is contain the many machine leaning algorithms. It is provide the facility to…

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## 137 Citations

### Performance Evaluation of Clustering Algorithms

- Computer Science
- 2013

This paper compares various clustering algorithms for data mining using Weka tool, a data mining tool that provides the facility to classify and cluster the data through machine leaning algorithms.

### Computational Time Analysis of K-mean Clustering Algorithm

- Computer Science
- 2017

The aim of this research is to analyze the computation time of k-mean clustering by varying the sample rate using stopwatch for time measurement.

### A Comparative Study Of Document Clustering

- Computer Science
- 2013

This paper is studying various clustering algorithms for the documents by using weka, which contains many machine learning algorithms for collecting a set of documents into group called clusters.

### Usage Apriori and clustering algorithms in WEKA tools to mining dataset of traffic accidents

- Computer Science
- 2018

Results shows that the Apriori algorithm is better than the EM cluster algorithm, which was implemented for traffic dataset to discover the factors, which causes accidents.

### Performance Evaluation of Clustering Algorithm Using Different Datasets

- Computer Science
- 2015

The four major clustering algorithms namely Simple K-mean, DBSCAN, HCA and MDBCA are analyzed and the performance of these four techniques are presented and compared using a clustering tool WEKA.

### Comparative Study and Performance Analysis of Clustering Algorithms

- Computer Science
- 2016

Results of the experiments suggest that Self-Organizing Maps (SOM) is more robust to outlier than the k-means method.

### Comparison the Various Clustering and Classification Algorithms of WEKA Tools

- Computer Science
- 2014

This paper presents the comparison of different classification and clustering techniques using Waikato Environment for Knowledge Analysis or in short, WEKA, and the algorithm or methods tested are DBSCAN,EM & K-MEANS clustering algorithms.

### Survey of Different Data Clustering Algorithms

- Computer Science
- 2018

Five clustering algorithms namely Simple KMeans, Density Based clustering, Filtered Cluster, Farthest First, and Expectation Maximization for Individual household electric power consumption dataset are presented.

### Performance Enhancement of K-Means Clustering Algorithms for High Dimensional Data sets

- Computer Science
- 2014

This paper proposes a method for making the K-Means algorithm more effective and efficient; so as to get better clustering with reduced complexity.

### Comparison of Different Classification Techniques Using WEKA for Hematological Data

- Computer Science
- 2015

The thesis main aims to show the comparison of different classification algorithms using Waikato Environment for Knowledge Analysis or in short, WEKA and find out which algorithm is most suitable for user working on hematological data.

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