



'''simple docstring'''





from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier

# Load iris file
lowercase_			=  load_iris()
iris.keys()


print(F"""Target names: \n {iris.target_names} """)
print(F"""\n Features: \n {iris.feature_names}""")

# Train set e Test set
lowercase_	, lowercase_	, lowercase_	, lowercase_			=  train_test_split(
    iris["data"], iris["target"], random_state=4
)

# KNN

lowercase_			=  KNeighborsClassifier(n_neighbors=1)
knn.fit(X_train, y_train)

# new array to test
lowercase_			=  [[1, 2, 1, 4], [2, 3, 4, 5]]

lowercase_			=  knn.predict(X_new)

print(
    F"""\nNew array: \n {X_new}\n\nTarget Names Prediction: \n"""
    F""" {iris['target_names'][prediction]}"""
)








'''simple docstring'''





from math import gcd




def lowerCAmelCase  (__A = 12_000):



     """simple docstring"""



     _a     =  0
     for d in range(max_d + 1):
          for n in range(d // 3 + 1  ,     (d + 1) // 2):
               if gcd(__A  ,     __A) == 1:
                    fractions_number += 1
     return fractions_number


if __name__ == "__main__":
  print(F"""{solution() = }""")



