Different Combinations of Fs Algorithms and Classifiers on Datasets IT Assignment Help

Assignment Task

Task    

You should test different combinations of FS (3 methods) and classifiers (4 methods) in your project and record the obtained accuracy and f-measure in the given table. You may use any available tool such as available machine learning libraries and open source codes on Github.

You should also follow the given instructions and cross-validate the experiments on the given 13 datasets.

1. You’ve to use the algorithms and classifiers for FS10.

2. Identify the approximate accuracy and time taken wile testing different combinations of FS algorithms and classifiers on datasets

3. The excel template should be filled up end to end as per the instructions shared.

4. Need to test with different number of features selected until there is no significant improvisation and mention same in template. Please share which number you have started with while testing and a graph plot of accuracy of each datasets is required depicting same.

5. Need 10-fold cross – validation and then computation of accuracy and f-measure is to be done at each cross level with 2 sections: Baseline and with feature selection as mentioned in Point 3(f) of instructions file and must be filled in template as well.

6. The above must be done with all 13 datasets.

7. Also, after all is done, provide all files to install on our computers with end-to-end understanding of the code, workings and template filling as I have to give demo to the whole class where we will be asked cross-questions and live running.

8. Please share the references of the code as we need to mention citations in our project report for the same.

9. The accuracy (%) on the template should be very high.

10. Provide Code files and output files

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