ISSN 2394-5125
 

Research Article 


DIABETES PREDICTION WITH WEKA TOOL

Dr. Pankaj Bhambri, Dr. Vijay Kumar Sinha, Dr. Inderjit Singh.

Abstract
Data mining is one of the matured areas of research which is rapidly growing. It is not an ordinary analysis. It
helps in predicting the future by discovering and identifying the different valuable patterns in large collections of given
data sets. It can also be defined as a process of uncovering previously unknown, precious and valuable patterns and
regularities in large chunks of the industrial and business data.
The term data mining is misnomer which means to extract the information and not the data. It can extract the
information from large sets of different formats of data stored at desperate locations. The extracted knowledge then can
be used to predict the future of the organizations, which has provided the data. There are many different data mining
techniques available that researchers can use to extract the required information. Knowledge discovery in databases is the
term which is associated and interlinked with data mining. Some researchers believe that data mining itself is a
knowledge discovery in database process but some say that data mining is an important step of knowledge discovery
process which is base of using this. Classification, clustering, association rule mining, neural networks, genetic
algorithm, memory based reasoning, link analysis and decision trees are the major ways in which data mining can be
used. Many different algorithms under these major data mining techniques had already been used by researchers
including J48, Nave Bayes, ZeroR, k-Nearest Neighbors, Neural Networks, Decision Tree, Support Vector Machine etc.
The data mining concepts are cleared in the book by Witten and Frank. In this study latter three techniques are
implemented.

Key words: Phylogenetic Tree, Orthology, Paralogy, Multiple Sequence Alignment


 
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How to Cite this Article
Pubmed Style

Dr. Pankaj Bhambri, Dr. Vijay Kumar Sinha, Dr. Inderjit Singh. DIABETES PREDICTION WITH WEKA TOOL . JCR. 2020; 7(9): 2366-2371. doi:10.31838/jcr.07.09.384


Web Style

Dr. Pankaj Bhambri, Dr. Vijay Kumar Sinha, Dr. Inderjit Singh. DIABETES PREDICTION WITH WEKA TOOL . http://www.jcreview.com/?mno=107412 [Access: April 18, 2021]. doi:10.31838/jcr.07.09.384


AMA (American Medical Association) Style

Dr. Pankaj Bhambri, Dr. Vijay Kumar Sinha, Dr. Inderjit Singh. DIABETES PREDICTION WITH WEKA TOOL . JCR. 2020; 7(9): 2366-2371. doi:10.31838/jcr.07.09.384



Vancouver/ICMJE Style

Dr. Pankaj Bhambri, Dr. Vijay Kumar Sinha, Dr. Inderjit Singh. DIABETES PREDICTION WITH WEKA TOOL . JCR. (2020), [cited April 18, 2021]; 7(9): 2366-2371. doi:10.31838/jcr.07.09.384



Harvard Style

Dr. Pankaj Bhambri, Dr. Vijay Kumar Sinha, Dr. Inderjit Singh (2020) DIABETES PREDICTION WITH WEKA TOOL . JCR, 7 (9), 2366-2371. doi:10.31838/jcr.07.09.384



Turabian Style

Dr. Pankaj Bhambri, Dr. Vijay Kumar Sinha, Dr. Inderjit Singh. 2020. DIABETES PREDICTION WITH WEKA TOOL . Journal of Critical Reviews, 7 (9), 2366-2371. doi:10.31838/jcr.07.09.384



Chicago Style

Dr. Pankaj Bhambri, Dr. Vijay Kumar Sinha, Dr. Inderjit Singh. "DIABETES PREDICTION WITH WEKA TOOL ." Journal of Critical Reviews 7 (2020), 2366-2371. doi:10.31838/jcr.07.09.384



MLA (The Modern Language Association) Style

Dr. Pankaj Bhambri, Dr. Vijay Kumar Sinha, Dr. Inderjit Singh. "DIABETES PREDICTION WITH WEKA TOOL ." Journal of Critical Reviews 7.9 (2020), 2366-2371. Print. doi:10.31838/jcr.07.09.384



APA (American Psychological Association) Style

Dr. Pankaj Bhambri, Dr. Vijay Kumar Sinha, Dr. Inderjit Singh (2020) DIABETES PREDICTION WITH WEKA TOOL . Journal of Critical Reviews, 7 (9), 2366-2371. doi:10.31838/jcr.07.09.384