Answer the following questions for conducting the classification for the well$-$known $$iris$$ data set.

Here, the output variable is $$Species$$ with three classes: setosa, versicolor, virginica. Use k$-$fold $($k$=5$ or $10)$ or hold$-$out $($No$.$ of replication$=50)$ method for the split of train $($e$.$g$.60\%)$ and test $($e$.$g$.40\%)$ sets.

$1)$ Compare the prediction results $($measure: accuracy$)$ on the test set using the five machine learning methods $($i$.$e$.$ DNN$,$ random forest, XGBoost, SVM and multinomial logistic regression$).$

Here, DNN$,$ deep neural networks; SVM$,$ support vector machine.

$2)$ Summarize the prediction results using the mean, median and standard deviation of accuracies and the corresponding box plot.

$3)$ Explain the prediction results.

Please give detail python code and results after run code.