Diabetes | feature- selection

[Anuragsarkar12]

Description

Performed Feature Selection
This PR does the following:

• Compared the Chi-square values and f-statistic values for all features in different plots
• Used f-statistic in SelectKBest and Recursive Feature Elimination with Cross Validation to create two new datasets
• Applied Random Forest Classifier with hyperparameter tuning on both the datasets and compared the model accuracies

Checklist

Make sure to check off all the items before submitting. Mark with [x] if done.

• I have performed a self-review of my code
• I have commented my code, particularly in hard-to-understand areas
• My changes generate no new warnings
• I am working on this issue under GSSOC

[github-actions]

Great job, @Anuragsarkar12! 🎉 Thank you for submitting your pull request. Your contribution is valuable and we appreciate your efforts to improve our project.

We will promptly review your changes and offer feedback. Keep up the excellent work! Kindly remember to check our contributing guidelines

[SrijanShovit]

First do feature selection properly then jump into prediction.

[Anuragsarkar12]

Could you provide me some suggestions as to what I should use further for feature selection

[SrijanShovit]

https://github.com/SrijanShovit/HealthLearning/blob/main/Metabolic%20Syndrome%20Prediction/metabolic_syndrome_predict.ipynb

Moreover, feature selection is not what I asked for in the issue. Feature Importance is different.

[Anuragsarkar12]

Okay,I'll make the appropriate changes

[SrijanShovit]

any updates @Anuragsarkar12

[Anuragsarkar12]

I am actually out of town so I am not able to work on it, I'll return tomorrow and will make the changes within a couple of days

[github-actions]

This issue has been automatically closed because it has been inactive for more than 7 days. If you believe this is still relevant, feel free to reopen it or create a new one. Thank you!