

'''simple docstring'''

def 				lowercase (					__magic_name__ = 99_8001							):



     '''simple docstring'''







     for number in range(n - 1			,   9999			,   -1							):
          UpperCAmelCase		:							Dict        =       str(__magic_name__							)

          # checks whether 'str_number' is a palindrome.
          if str_number == str_number[::-1]:
               UpperCAmelCase		:							Optional[Any]        =       999

               # if 'number' is a product of two 3-digit numbers
               # then number is the answer otherwise fetch next number.
               while divisor != 99:
                    if (number % divisor == 0) and (len(str(number // divisor							)							) == 3.0):
                         return number
                    divisor -= 1
     raise ValueError("That number is larger than our acceptable range."							)


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



'''simple docstring'''

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

# Load iris file
a       :      List[Any]  	=			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
a	,						a	,						a	,						a       :      List[Any]  	=			train_test_split(
    iris["data"], iris["target"], random_state=4
)

# KNN

a       :      Tuple  	=			KNeighborsClassifier(n_neighbors=1)
knn.fit(X_train, y_train)

# new array to test
a       :      Optional[int]  	=			[[1, 2, 1, 4], [2, 3, 4, 5]]

a       :      Tuple  	=			knn.predict(X_new)

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