Hybrid Model of whale Optimization Merged Decision Tree For Classification

Project Title

Hybrid Model of whale Optimization Merged Decision Tree For Classification

Project Area of Specialization Artificial IntelligenceProject Summary

Feature Selection (FS) in data mining is one of the most challenging and most important activities in pattern recognition. The problem of choosing a feature is to find the most important subset of the main attributes in a specific domain, and its main purpose is removing additional or unrelated features, and ultimately improving the accuracy of the classification algorithms. As a result, the problem of FS can be considered as an optimization problem, and use metaheuristic algorithms to solve it..

Project Objectives

We propose a novel method for feature selection utilizing Whale optimization combined with a decision tree as the classifier to select a small number of informative gene from the thousands of gene in the data that can contribute to identifying cancers.

Project Implementation Method

We uses Pyhton language in Spyder IDE for implementation of  our project and a dedicated server will be use.

Benefits of the Project

we wants to implement our project in different industries but specially it will be design for hospital and our aim is diagnose of brest cancer disease.

Technical Details of Final Deliverable

It will Help the doctors to identify the brest cancer of a patient and also classify  where  the cancer is benign or melignent.

Final Deliverable of the Project Hardware SystemCore Industry MedicalOther Industries Finance , Health Core Technology Artificial Intelligence(AI)Other Technologies Big DataSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	60000
Hardware	Equipment	1	60000	60000