An Ensemble Model of Machine Learning Algorithms for the Severity of Sickle Cell Disease (Scd) Among Paediatrics Patients
Journal Title: Computer Reviews Journal - Year 2018, Vol 2, Issue 0
Abstract
This study was motivated at developing an ensemble of 3 supervised machine learning algorithms for the assessment of the severity of sickle cell disease (SCD) among paediatric patients. The study collected data from a tertiary hospital in south-western Nigeria following the identification of variables required for assessing the severity of SCD. The study also adopted the use of 3 supervised machine learning algorithms namely: naïve Bayes (NB), C4.5 decision trees (DT) and support vector machines (SVM) for creating the ensemble model using a 10-fold cross validation technique. The models were created by adopting the algorithms in isolation and in combination of 2 and 3 which were compared. The developed models were evaluated in order to present the model with the best performance. The results of the study showed that using an ensemble of DT and NB alone provided the best performance. The study has implications in presenting a model for improving the assessment of the severity of SCD among paediatric patients in Nigeria.
Authors and Affiliations
Balogun Jeremiah Ademola, Aderounmu Temilade, Egejuru Ngozi Chidozie, Idowu Peter Adebayo
Keywords
Related Articles
- EP ID EP655256
- DOI -
- Views 130
- Downloads 0
Radial Basis Function Neural Networks : A Review
Radial Basis Function neural networks (RBFNNs) represent an attractive alternative to other neural network models. One reason is that they form a unifying link between function approximation, regularization, noisy interp...
Evolution and Trends in the Educational Model of Distance Education in Mexico, Towards an Education 4.0
Currently, the development of increasingly sophisticated platforms to carry out Distance Education (ED) at a higher level is underway. Through the implementation of different types of emerging technologies, and with this...
Efficiency Analysis of Hybrid Fuzzy C-Means Clustering Algorithms and their Application to Compute the Severity of Disease in Plant Leaves
Data clustering has a wide range of application varying from medical image analysis, social network analysis, market segmentation, search engines, recommender systems and image processing. A clustering algorithm should b...
Testing Multiple Strategy Human Optimization based Artificial Human Optimization Algorithms
Recently a new trend titled ‘Artificial Human Optimization’ has become popular in Evolutionary Computing Domain. More than 30 papers were published in this new field proposed in December 2016. ‘Hassan Satish Particle Swa...
A Theoretical Overview of Mobile Networks Environment in Ecuador Prior To 5G
Many countries in the Latin American region experience the technology gap when new technologies are either developing or in testing scenarios. Telecommunications services provider must be encouraged, allowing universal a...