Implement your own logistic regression and classify the iris data into setosa or non-setosa. You are supposed to write y

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Implement your own logistic regression and classify the irisdata into setosa or non-setosa. You are supposed to write your ownlogit function and implement gradient descent to learn optimalweights. Then using this weight classify the entire data set assetosa or non-setosa. We encourage you not to use logisticregression implementation of scikit learn package. (If you arefacing too much difficulty during implementation you can usepackages no marks will be deducted for that. However, please tryyour best to avoid using packages. ) Report how much accuracyyou got. You can try your logistic regression code on some otherdataset as well for binary classification.
Implement a feature selection algorithm to select the 5 bestfeatures of OnlineNewsPopularity data set.
Here is link todataset: https://archive.ics.uci.edu/ml/machine- ... larity.zip