Active Prediction of Heart Disease using Techniques of Hybrid Machine Learning

Abstract

<jats:p>In this world one of the main sources of death is dependent on coronary illness happens in both men and women. It might cause because of the absence of data or inadequate data gave by the doctor in light of some innovation issue or because the prediction level is low. We have additionally observed the utilization of ML methods in ongoing advancements in different Internet of Things (IoT) fields. Different examinations just give a brief look at anticipating coronary illness utilizing ML methods. In this paper, we are looking at how this hybrid method is better than utilizing a single calculation which gives higher exactness up to 88.7% than contrast with different procedures</jats:p>

Multi-Objective Dynamic Software Project Scheduling: A Novel Approach to Handle Employee’s Addition

“…However, these techniques may fail due to distinctive characteristics of software projects such as nature of the team, application being built and customers. Moreover, these cannot effectively handle situations in which two or more projects share available resources, and also require subjective information to generate an effective project schedule [11]. Further, to ensure the sustainable software development in an uncertain and dynamic environment, the risk mitigation strategies must be adopted to ensure business continuity.…”