Please help with the following questions:

def exercise02(new_observations):

'''

Data set: Iris

Fit the Iris data set into a kNN model with neighbors=5 and predict the

category of observations passed in

argument new_observations. Return back the target names of each

prediction (and not their encoded values,

i.e. return setosa instead of 0).

'''

# ------ Place code below here \/ \/ \/ ------

# ------ Place code above here /\ /\ /\ ------

return iris_predictions

# 15 points

def exercise03(neighbors,split):

'''

Data set: Iris

Split the Iris data set into a train / test model with the split ratio

between the two established by

the function parameter split.

Fit KNN with the training data with number of neighbors equal to the

function parameter neighbors

Generate and return back an accuracy score using the test data was split

out

'''

random_state = 21

# ------ Place code below here \/ \/ \/ ------

# ------ Place code above here /\ /\ /\ ------

return knn_score