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Prediction of Diabetes Diseases by Building a Machine Learning Model
http://hdl.handle.net/20.500.12678/0000007432
http://hdl.handle.net/20.500.12678/000000743225dc4ffb-8a05-443b-9180-1ed0a7b63933
d8a01011-7d41-4906-b1e1-8c2dc87e6fa6
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Prediction_of_Diabetes_Diseases_by_Building_a_Machine_Learning_Model.pdf (522 KB)
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Publication type | ||||||
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Journal article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Prediction of Diabetes Diseases by Building a Machine Learning Model | |||||
Language | en | |||||
Publication date | 2019-12-13 | |||||
Authors | ||||||
Hnin Ei Ei Cho | ||||||
Nan Yu Hlaing | ||||||
Description | ||||||
The aim of this paper is to compare the six different learning algorithms in order to predict diabetes in patients more accurately using the Pima-Indians-Diabetes Dataset obtained from UCI Machine Learning repository site, the Centre for Machine Learning and Intelligent Systems at the University of California, Irvine | ||||||
Keywords | ||||||
parsing, stochastic parsing, stochastic context free grammar, parse tree. | ||||||
Journal articles | ||||||
No-1 | ||||||
University Journal of Research and Innovation, UCS(Pakokku) | ||||||
9-14 | ||||||
Vol-1 |