Python/machine_learning/polymonial_regression.py
pre-commit-ci[bot] 3f9150c1b2
[pre-commit.ci] pre-commit autoupdate (#8294)
* [pre-commit.ci] pre-commit autoupdate

updates:
- [github.com/charliermarsh/ruff-pre-commit: v0.0.255 → v0.0.257](https://github.com/charliermarsh/ruff-pre-commit/compare/v0.0.255...v0.0.257)

* Fix PLR1711 Useless  statement at end of function

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Christian Clauss <cclauss@me.com>
2023-03-20 22:16:13 +01:00

45 lines
1.2 KiB
Python

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
dataset = pd.read_csv(
"https://s3.us-west-2.amazonaws.com/public.gamelab.fun/dataset/"
"position_salaries.csv"
)
X = dataset.iloc[:, 1:2].values
y = dataset.iloc[:, 2].values
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)
poly_reg = PolynomialFeatures(degree=4)
X_poly = poly_reg.fit_transform(X)
pol_reg = LinearRegression()
pol_reg.fit(X_poly, y)
# Visualizing the Polymonial Regression results
def viz_polymonial():
plt.scatter(X, y, color="red")
plt.plot(X, pol_reg.predict(poly_reg.fit_transform(X)), 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