Data Mining Application for Finding Patterns: Survey of Large Data Research Tools
Issue:
Volume 3, Issue 2, April 2017
Pages:
14-21
Received:
1 November 2017
Accepted:
21 November 2017
Published:
5 December 2017
Abstract: Data Mining is now a common method for mining data from databases and finding out patterns from the data. Today many organizations are using data mining techniques. In this paper concepts and techniques such as Neural Network, Decision Tree, Clustering, Association Rule, Clustering and many more techniques of Data Mining is reviewed. This paper focuses how different techniques of Data Mining are used in different applications for finding out patterns from the data taken from the data base.
Abstract: Data Mining is now a common method for mining data from databases and finding out patterns from the data. Today many organizations are using data mining techniques. In this paper concepts and techniques such as Neural Network, Decision Tree, Clustering, Association Rule, Clustering and many more techniques of Data Mining is reviewed. This paper foc...
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Off-Line Handwritten Character Recognition System Using Support Vector Machine
Gauri Katiyar,
Ankita Katiyar,
Shabana Mehfuz
Issue:
Volume 3, Issue 2, April 2017
Pages:
22-28
Received:
24 October 2017
Accepted:
21 November 2017
Published:
13 December 2017
Abstract: Selection of classifiers and feature extraction methods has a prime role in achieving best possible classification accuracy in character recognition system. Issues of character recognition system related to choice of classifiers and feature extraction methods can be resolved through these objectives. In this proposed work an efficient Support Vector Machine based off-line handwritten character recognition system has been developed. The experiments have been performed using well known standard database acquired from CEDAR, also seven different approaches of feature extraction techniques have been proposed to construct the final feature vector. It is evident from the experimental results that the performance of Support Vector Machine outperforms other state of art techniques reported in literature.
Abstract: Selection of classifiers and feature extraction methods has a prime role in achieving best possible classification accuracy in character recognition system. Issues of character recognition system related to choice of classifiers and feature extraction methods can be resolved through these objectives. In this proposed work an efficient Support Vecto...
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