





"""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       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		return (data["data"], data["target"])


def       a__					(					_SCREAMING_SNAKE_CASE  ,	_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	XGBClassifier()
		classifier.fit(__UpperCamelCase  ,	__UpperCamelCase    )
		return classifier


def       a__					(					):




		"""simple docstring"""


		UpperCamelCase   =	load_iris()
		UpperCamelCase   =	data_handling(__UpperCamelCase    )
		UpperCamelCase   =	train_test_split(
		    __UpperCamelCase  ,	__UpperCamelCase  ,	test_size=0.25    )

		UpperCamelCase   =	iris["""target_names"""]

		# Create an XGBoost Classifier from the training data
		UpperCamelCase   =	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()













"""simple docstring"""





import os

from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home


lowerCAmelCase__     			=			HUGGINGFACE_HUB_CACHE


lowerCAmelCase__     			=			'''config.json'''
lowerCAmelCase__     			=			'''diffusion_pytorch_model.bin'''
lowerCAmelCase__     			=			'''diffusion_flax_model.msgpack'''
lowerCAmelCase__     			=			'''model.onnx'''
lowerCAmelCase__     			=			'''diffusion_pytorch_model.safetensors'''
lowerCAmelCase__     			=			'''weights.pb'''
lowerCAmelCase__     			=			'''https://huggingface.co'''
lowerCAmelCase__     			=			default_cache_path
lowerCAmelCase__     			=			'''diffusers_modules'''
lowerCAmelCase__     			=			os.getenv('''HF_MODULES_CACHE''', os.path.join(hf_cache_home, '''modules'''))
lowerCAmelCase__     			=			['''fp16''', '''non-ema''']
lowerCAmelCase__     			=			'''.self_attn'''






