mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-11-24 05:21:09 +00:00
2197bfa029
* #840 adds polymonial regression program in python * Update polymonial_regression.py * Update polymonial_regression.py
38 lines
1.2 KiB
Python
38 lines
1.2 KiB
Python
import matplotlib.pyplot as plt
|
|
import pandas as pd
|
|
|
|
# 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
|
|
|
|
|
|
# Splitting the dataset into the Training set and Test set
|
|
from sklearn.model_selection import train_test_split
|
|
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)
|
|
|
|
|
|
# Fitting Polynomial Regression to the dataset
|
|
from sklearn.preprocessing import PolynomialFeatures
|
|
from sklearn.linear_model import LinearRegression
|
|
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()
|
|
return
|
|
viz_polymonial()
|
|
|
|
# Predicting a new result with Polymonial Regression
|
|
pol_reg.predict(poly_reg.fit_transform([[5.5]]))
|
|
#output should be 132148.43750003
|