Research Project on " Ant Colony Improvement (ACI) approach for Automated Disease Diagnoses using fuzzy logic"

Summary- This research proposes a diagnosis-oriented clinical decision assistance system based on ACI and fuzzy inference. The ACI technique is used in conjunction with fuzzy logic to extract rules from a dataset and then improve them. The fuzzy inference engine is used to classify test data based on an enhanced set of rules. k-fold cross validation should also be used.

1) I need someone who has the knowledge of implementing "Ant Colony Improvement" (ACI) technique on Machine Learning classification problem of disease diagnoses.

2) The person must implement ACI with and without fuzzy logic on three different dataset (related to classification problem of machine learning).

3) I'll provide the datasets on which the above task will be done.

4) The person must also explain me the working of the above technique in detail.

5) The above code must be implemented in MATLAB.

6) The person should also submit a report on the above, stating that why this research is important? what is novelty in it? Comparison with other approaches etc etc.

Note: Kindly do not ask me to increase the bid amount.