
'''simple docstring'''
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier






def      UpperCamelCase_				(      A__						):
	return (data["data"], data["target"])






def      UpperCamelCase_				(      A__  ,      A__						):
	a_      				=						XGBClassifier()
	classifier.fit(A__  ,      A__						)
	return classifier






def      UpperCamelCase_				(      ):
	a_      				=						load_iris()
	a_				,  a_      				=						data_handling(A__						)
	a_				,  a_				,  a_				,  a_      				=						train_test_split(
	    A__  ,      A__  ,      test_size=0.25						)

	a_      				=						iris["""target_names"""]

	# Create an XGBoost Classifier from the training data
	a_      				=						xgboost(A__  ,      A__						)

	# Display the confusion matrix of the classifier with both training and test sets
	ConfusionMatrixDisplay.from_estimator(
	    A__  ,      A__  ,      A__  ,      display_labels=A__  ,      cmap="""Blues"""  ,      normalize="""true"""  ,      )
	plt.title("""Normalized Confusion Matrix - IRIS Dataset"""						)
	plt.show()


if __name__ == "__main__":
		import doctest

		doctest.testmod(verbose=True)
		main()


'''simple docstring'''
def      UpperCamelCase_				(      A__  ,      A__  ,      A__						):

	def count_of_possible_combinations(A__						) -> int:
		if target < 0:
			return 0
		if target == 0:
			return 1
		return sum(count_of_possible_combinations(target - item						) for item in array						)

	return count_of_possible_combinations(A__						)






def      UpperCamelCase_				(      A__  ,      A__  ,      A__						):

	def count_of_possible_combinations_with_dp_array(
	    A__  ,      A__						) -> int:
		if target < 0:
			return 0
		if target == 0:
			return 1
		if dp_array[target] != -1:
			return dp_array[target]
		a_      				=						sum(
		    count_of_possible_combinations_with_dp_array(target - item  ,      A__						)
		    for item in array						)
		a_      				=						answer
		return answer

	a_      				=						[-1] * (target + 1)
	return count_of_possible_combinations_with_dp_array(A__  ,      A__						)






def      UpperCamelCase_				(      A__  ,      A__  ,      A__						):
	a_      				=						[0] * (target + 1)
	a_      				=						1

	for i in range(1  ,      target + 1						):
		for j in range(A__						):
			if i - array[j] >= 0:
				dp_array[i] += dp_array[i - array[j]]

	return dp_array[target]


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		lowercase__											=3
		lowercase__											=5
		lowercase__											=[1, 2, 5]
		print(combination_sum_iv(n, array, target))
