International Journal of Advance Computational Engineering and Networking (IJACEN)
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Statistics report
Aug. 2020
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 87
Paper Published : 1231
No. of Authors : 3095
  Journal Paper

Paper Title
Improving Classification Efficiency Of Large Data Sets Using New Supervised Learning Algorithm

Now a day’s information plays a great role in the development of a country in particular or world in general. This information should be organized in the form which is more important for its user. To organize this data, we might need data mining concepts, which discover the knowledge by analyzing the large volumes of data from various dimensions and summarizing it into useful information. It is used to identify hidden patterns in a large dataset. Classification methods are techniques that classify data item into predefined class label based on the training dataset. Classification method is one of the most useful techniques in data mining to build classification models from an input dataset. Basically classification can be done either using supervised learning or unsupervised learning methods.In this paper, we have worked with different data mining supervised classification algorithms and find out the efficiency and improve the performance of large datasets based on new supervised learning algorithm. Keywords- Classification, Data Mining, New Classification Technique, Lazy Learner.

Author - Radha Krishna Bokka, Vuda Sreenivasarao

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| Published on 2015-03-03
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