
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor





def 			lowerCamelCase_ (				lowerCamelCase__    ):
				return (data["data"], data["target"])





def 			lowerCamelCase_ (				lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__    ):
				lowerCamelCase_						=			XGBRegressor(verbosity=0	, random_state=4_2    )
				xgb.fit(lowerCamelCase__	, lowerCamelCase__    )
				# Predict target for test data
				lowerCamelCase_						=			xgb.predict(lowerCamelCase__    )
				lowerCamelCase_						=			predictions.reshape(len(lowerCamelCase__    )	, 1    )
				return predictions





def 			lowerCamelCase_ (				):
				lowerCamelCase_						=			fetch_california_housing()
				lowerCamelCase_	,    lowerCamelCase_						=			data_handling(lowerCamelCase__    )
				lowerCamelCase_	,    lowerCamelCase_	,    lowerCamelCase_	,    lowerCamelCase_						=			train_test_split(
				    lowerCamelCase__	, lowerCamelCase__	, test_size=0.25	, random_state=1    )
				lowerCamelCase_						=			xgboost(lowerCamelCase__	, lowerCamelCase__	, lowerCamelCase__    )
				# Error printing
				print(F'Mean Absolute Error : {mean_absolute_error(lowerCamelCase__	, lowerCamelCase__    )}'    )
				print(F'Mean Square Error  : {mean_squared_error(lowerCamelCase__	, lowerCamelCase__    )}'    )


if __name__ == "__main__":
			import doctest

			doctest.testmod(verbose=True)
			main()




# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

__A				='''2.13.1'''

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse('''3.7'''):
			raise ImportWarning(
			    '''To use `datasets`, Python>=3.7 is required, and the current version of Python doesn\'t match this condition.'''
			)

if version.parse(pyarrow.__version__).major < 8:
			raise ImportWarning(
			    '''To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn\'t match this condition.\n'''
			    '''If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`.'''
			)

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

__A				=concatenate_datasets
__A				=DownloadConfig
__A				=DownloadManager
__A				=DownloadMode
__A				=DownloadConfig
__A				=DownloadMode
__A				=DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager


