In this assignment, you fit different classifiers $($linear regression, SVM$,$ Neural Network and Naive Bayesian$)$ on iris dataset $($use sklearn.datasets.load$\_$irisLinks to an external site. to load it$).$

Step $1$: use assignment $4$ draft.py to draw the following six scatter plots depicting the way different classifiers perform on the iris dataset which has $50$ samples for each of its three classes$($labels$).$ These plots figure each class with a different color $($red$,$ blue, white$)$

Step $3$: $(25$ points$)$ Compare the following six classifiers by drawing a grid of six plots similar to the one you obtained from step $1$:

linear regression

linearSVC

GaussianNB w$/$ var$\_$smoothing$=2$e$1$

GaussianNB w$/$ var$\_$smoothing$=1$e$1$

GaussianNB w$/$ var$\_$smoothing$=1$e$0$

GaussianNB w$/$ var$\_$smoothing$=1$e$-1$

Step $4$: $(25$ points$)$ Compare six variations of SVM classifiers with kernels $[\text{'}$sigmoid$\text{'},\text{'}$rfb$\text{'}],$ and gamma values $[1$e$-1,1$e$0,1$e$2]$ by drawing a grid of six plots similar to the one you obtained from step $1.$

Step $5$: $(25$ points$)$ Compare eight variations of neural network MLP classifiers with default alpha $(1$e$-4),$ solvers $[\text{'}$adam$\text{'},\text{'}$lbfgs$\text{'}],$ activation $[\text{'}$logistic$\text{'},$ 'relu'$]$ and layers $[(30,30),(10,5)]$ by drawing a grid of eight plots similar to the one you obtained from step $1.$

Submissions

Please submit a single zip file compressing the following:$3,5,7],$ and gamma values $[\mathrm{.}3,\mathrm{.}5]$ by drawing a grid of six plots similar to the one you obtained from step $1.$

assignment $4.$png

Step $2$: $(25$ points$)$

assginment $4.$py $($source code$)$

report.pdf containing the plots drawn in steps $1$ to $5.$