from sklearn.datasets import load$\_$iris

import numpy as np

from sklearn.model$\_$selection import train$\_$test$\_$split

iris $=$ load$\_$iris$()$

feature $=$ iris.data$[$:$100]$

ans $=$ iris.target$[$:$100]$

X$\_$train, X$\_$test, y$\_$train, y$\_$test $=$ train$\_$test$\_$split$($feature$,$ ans, test$\_$size$=0\mathrm{.}3,$ random$\_$state$=1)$

for epoch in range$($epochs$)$:

$[$blink$]$

print$($accuracy$)$

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$1.$ Please find a code to verify the performance of the artificial neural network model. Objective functions, hyperparameters, optimization methods, etc. are freely available,

but packages other than the above form are not available.

$2.$ Please print out the code that verifies the performance of the artificial neural network model. Please print out the accuracy,

which is the percentage of the predicted out of an additional $30$ test samples