






'''simple docstring'''




import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression

# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split

# Fitting Polynomial Regression to the dataset
from sklearn.preprocessing import PolynomialFeatures

# Importing the dataset
lowerCAmelCase__          =						pd.read_csv(
    'https://s3.us-west-2.amazonaws.com/public.gamelab.fun/dataset/'
    'position_salaries.csv'
)
lowerCAmelCase__          =						dataset.iloc[:, 1:2].values
lowerCAmelCase__          =						dataset.iloc[:, 2].values


lowerCAmelCase__       ,							lowerCAmelCase__       ,							lowerCAmelCase__       ,							lowerCAmelCase__          =						train_test_split(X, y, test_size=0.2, random_state=0)


lowerCAmelCase__          =						PolynomialFeatures(degree=4)
lowerCAmelCase__          =						poly_reg.fit_transform(X)
lowerCAmelCase__          =						LinearRegression()
pol_reg.fit(X_poly, y)







def       __UpperCAmelCase						(  )							->     int:
		plt.scatter(lowerCamelCase_     ,      lowerCamelCase_     ,      color='red')
		plt.plot(lowerCamelCase_     ,      pol_reg.predict(poly_reg.fit_transform(lowerCamelCase_))     ,      color='blue')
		plt.title('Truth or Bluff (Linear Regression)')
		plt.xlabel('Position level')
		plt.ylabel('Salary')
		plt.show()


if __name__ == "__main__":
		viz_polymonial()

		# Predicting a new result with Polymonial Regression
		pol_reg.predict(poly_reg.fit_transform([[5.5]]))
		# output should be 132148.43750003












'''simple docstring'''




from ..utils import DummyObject, requires_backends







class       __lowercase					(metaclass=__lowerCamelCase    ):
	_lowerCamelCase              =  ['''torch''', '''scipy''']

	def __init__(      self   :						List[Any]  ,					*UpperCAmelCase_   :						Any  ,					**UpperCAmelCase_   :						int):
			requires_backends(self  ,					['torch', 'scipy'])

	@classmethod
	def      __UpperCamelCase							(      cls   :						Union[str, Any]  ,					*UpperCAmelCase_   :						Any  ,					**UpperCAmelCase_   :						List[Any]):
			requires_backends(cls  ,					['torch', 'scipy'])





	@classmethod
	def      __UpperCamelCase							(      cls   :						Union[str, Any]  ,					*UpperCAmelCase_   :						Optional[Any]  ,					**UpperCAmelCase_   :						Any):
			requires_backends(cls  ,					['torch', 'scipy'])




