Data Classification Using Waikato Environment For Knowledge Analysis - Yeturu, Jahnavi
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Classification is a method of categorizing or assigning class labels to a pattern set under the supervision of a teacher. Classification is also called as supervised learning. The patterns are initially partitioned into training and test sets. Training set is used to train the classifier and the test set is used to evaluate the accuracy of a classifier. WEKA is open source software, which is developed by the University of Waikato in New Zealand. The system is written using object oriented language JAVA. There are different levels at which WEKA can be used. WEKA provides implementation of Data…mehr

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Produktbeschreibung
Classification is a method of categorizing or assigning class labels to a pattern set under the supervision of a teacher. Classification is also called as supervised learning. The patterns are initially partitioned into training and test sets. Training set is used to train the classifier and the test set is used to evaluate the accuracy of a classifier. WEKA is open source software, which is developed by the University of Waikato in New Zealand. The system is written using object oriented language JAVA. There are different levels at which WEKA can be used. WEKA provides implementation of Data Mining and Machine Learning Algorithms. WEKA Explorer is used for preprocessing, attribute selection, filtering, classification, clustering, association analysis, visualization etc. Experimentation using Waikato Environment for Knowledge Analysis has been performed for classification.
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Autorenporträt
Y. Jahnavi received her BTech from JNTU, MTech from Sri Venkateswara Univeristy, Tirupathi and PhD from GITAM,Visakhapatnam. She qualified GATE, APSET and NET examinations. She is a member of CSI, LMISTE etc. She is currently working as a Professor and Head in the dept. of CSE at GIST, AP, India. She has been publishing papers in various journals.