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 							lowerCAmelCase(     __lowerCamelCase						):
					return (data["data"], data["target"])
def 							lowerCAmelCase(     __lowerCamelCase				,    __lowerCamelCase						):
					__a		 =       XGBClassifier()
					classifier.fit(UpperCAmelCase_				,    UpperCAmelCase_						)
					return classifier
def 							lowerCAmelCase(     ):
					__a		 =       load_iris()
					__a ,				__a		 =       data_handling(UpperCAmelCase_						)
					__a ,				__a ,				__a ,				__a		 =       train_test_split(
					    UpperCAmelCase_				,    UpperCAmelCase_				,    test_size=0.25						)

					__a		 =       iris['target_names']

					# Create an XGBoost Classifier from the training data
					__a		 =       xgboost(UpperCAmelCase_				,    UpperCAmelCase_						)

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


if __name__ == "__main__":
	import doctest

	doctest.testmod(verbose=True)
	main()





from ..utils import DummyObject, requires_backends


class 						a__							(       metaclass=__snake_case		):
			A__    :       List[Any]        =      ['torch', 'transformers', 'onnx']



			def __init__(						self				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   Any:
								requires_backends(self				,						['torch', 'transformers', 'onnx']   )



			@classmethod
			def __SCREAMING_SNAKE_CASE							(						cls				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   Union[str, Any]:
								requires_backends(cls				,						['torch', 'transformers', 'onnx']   )







			@classmethod
			def __SCREAMING_SNAKE_CASE							(						cls				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   List[str]:
								requires_backends(cls				,						['torch', 'transformers', 'onnx']   )






class 						a__							(       metaclass=__snake_case		):
			A__    :       Union[str, Any]        =      ['torch', 'transformers', 'onnx']



			def __init__(						self				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   int:
								requires_backends(self				,						['torch', 'transformers', 'onnx']   )



			@classmethod
			def __SCREAMING_SNAKE_CASE							(						cls				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   int:
								requires_backends(cls				,						['torch', 'transformers', 'onnx']   )







			@classmethod
			def __SCREAMING_SNAKE_CASE							(						cls				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   Dict:
								requires_backends(cls				,						['torch', 'transformers', 'onnx']   )






class 						a__							(       metaclass=__snake_case		):
			A__    :       Dict        =      ['torch', 'transformers', 'onnx']



			def __init__(						self				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   Union[str, Any]:
								requires_backends(self				,						['torch', 'transformers', 'onnx']   )



			@classmethod
			def __SCREAMING_SNAKE_CASE							(						cls				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   Any:
								requires_backends(cls				,						['torch', 'transformers', 'onnx']   )







			@classmethod
			def __SCREAMING_SNAKE_CASE							(						cls				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   int:
								requires_backends(cls				,						['torch', 'transformers', 'onnx']   )






class 						a__							(       metaclass=__snake_case		):
			A__    :       Union[str, Any]        =      ['torch', 'transformers', 'onnx']



			def __init__(						self				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   Optional[Any]:
								requires_backends(self				,						['torch', 'transformers', 'onnx']   )



			@classmethod
			def __SCREAMING_SNAKE_CASE							(						cls				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   int:
								requires_backends(cls				,						['torch', 'transformers', 'onnx']   )







			@classmethod
			def __SCREAMING_SNAKE_CASE							(						cls				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   Union[str, Any]:
								requires_backends(cls				,						['torch', 'transformers', 'onnx']   )






class 						a__							(       metaclass=__snake_case		):
			A__    :       Dict        =      ['torch', 'transformers', 'onnx']



			def __init__(						self				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   Optional[int]:
								requires_backends(self				,						['torch', 'transformers', 'onnx']   )



			@classmethod
			def __SCREAMING_SNAKE_CASE							(						cls				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   Any:
								requires_backends(cls				,						['torch', 'transformers', 'onnx']   )







			@classmethod
			def __SCREAMING_SNAKE_CASE							(						cls				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   str:
								requires_backends(cls				,						['torch', 'transformers', 'onnx']   )






class 						a__							(       metaclass=__snake_case		):
			A__    :       Tuple        =      ['torch', 'transformers', 'onnx']



			def __init__(						self				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   int:
								requires_backends(self				,						['torch', 'transformers', 'onnx']   )



			@classmethod
			def __SCREAMING_SNAKE_CASE							(						cls				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   List[str]:
								requires_backends(cls				,						['torch', 'transformers', 'onnx']   )







			@classmethod
			def __SCREAMING_SNAKE_CASE							(						cls				,						*UpperCAmelCase				,						**UpperCAmelCase   )			->   Any:
								requires_backends(cls				,						['torch', 'transformers', 'onnx']   )




