The final objective of my Ph.D. work is to design Hybrid Model(s) for Disease Prediction on Health-Dataset (like statlog, cleveland heart dataset) by using Datamining/Machinelearning algorithms.
In Order to achieve that, i've to perform analysis of some algorithms (mentioned as objective)
I'm confused about what algorithms to choose for it and on what basis?
In this objective, i'll therotically study them and then implement/perform on WEKA/MATLAB.
Suggestions are Welcome. Please link some related work if possible.
Thanking you.
Dear Aman Sharma
Check these articles. They will help you
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Dear Aman,
At first, you have to consider that there is no panacea for all ML problems meaning that you have to select proper algorithms based on your dataset. For example, deep learning algorithms work well for categorical data and tree-based leaning algorithms work superior for tabular data. Moreover, if you have not-identically distributed unbalanced data you have to use federated learning including transfer learning. The story does not end here!
Sincerely,
Dear Aman Sharma
Check these articles. They will help you
Article Novel Feature Selection and Voting Classifier Algorithms for...
Article MbGWO-SFS: Modified Binary Grey Wolf Optimizer Based on Stoc...
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