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Predicting the Birth of Healthy Babies with Gestation Period Observations using Machine Learning Algorithms

K. Menaka1 , B. KeerthanaKani2

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-3 , Page no. 271-275, Mar-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i3.271275

Online published on Mar 31, 2019

Copyright © K. Menaka, B. KeerthanaKani . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: K. Menaka, B. KeerthanaKani, “Predicting the Birth of Healthy Babies with Gestation Period Observations using Machine Learning Algorithms,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.271-275, 2019.

MLA Style Citation: K. Menaka, B. KeerthanaKani "Predicting the Birth of Healthy Babies with Gestation Period Observations using Machine Learning Algorithms." International Journal of Computer Sciences and Engineering 7.3 (2019): 271-275.

APA Style Citation: K. Menaka, B. KeerthanaKani, (2019). Predicting the Birth of Healthy Babies with Gestation Period Observations using Machine Learning Algorithms. International Journal of Computer Sciences and Engineering, 7(3), 271-275.

BibTex Style Citation:
@article{Menaka_2019,
author = {K. Menaka, B. KeerthanaKani},
title = {Predicting the Birth of Healthy Babies with Gestation Period Observations using Machine Learning Algorithms},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2019},
volume = {7},
Issue = {3},
month = {3},
year = {2019},
issn = {2347-2693},
pages = {271-275},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3829},
doi = {https://doi.org/10.26438/ijcse/v7i3.271275}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i3.271275}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3829
TI - Predicting the Birth of Healthy Babies with Gestation Period Observations using Machine Learning Algorithms
T2 - International Journal of Computer Sciences and Engineering
AU - K. Menaka, B. KeerthanaKani
PY - 2019
DA - 2019/03/31
PB - IJCSE, Indore, INDIA
SP - 271-275
IS - 3
VL - 7
SN - 2347-2693
ER -

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Abstract

Machine learning is the most familiar division of Artificial Intelligence to perform exploratory data analysis tasks and to work out a variety of problems such as weather forecasting, drug discovery, encrypted image detection etc., This paper discusses about varieties of data mining classification algorithms that are commonly used to extract considerable knowledge from huge volumes of data. Identification of the healthiness of a baby with the observations during the gestation period of a mother requires various parameters to be taken into consideration during that period. Decision Tree (DT) algorithms could be very much helpful in predicting the healthiness of a baby. The numerical form of the data sets are taken and are fed to the DT algorithms to make calculations for the prediction of the healthiness of the baby. The data sets are taken and analyzed in the Waikato Environment for Knowledge Analysis (WEKA) platform.

Key-Words / Index Term

Data Mining, Knowledge Discovery, Classification Algorithms, WEKA

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