A Systematic Comparison and Evaluation of Supervised Machine Learning Classifiers Using Headache Dataset

摘要: The massive growth of data volume within the healthcare sector pushes current classical systems that were adapted to limit. Recent studies have focused on use machine learning methods develop extract knowledge from by means analysing, mining, pattern recognition, classification and prediction. Our research study reviews examines different supervised classifiers using headache dataset. Different statistical measures been used evaluate performance seven well-known classifiers. experimental indicated Decision Tree classifier achieved a better overall performance, followed Artificial Neural Network, Support Vector Machine k-Nearest Neighbor. This would determine most suitable for developing particular system is capable identifying primary disorders.