Browse Source

Ejemplo de regresión polinomial

master
parent
commit
face90f7ae
1 changed files with 20 additions and 0 deletions
  1. +20
    -0
      regresionpolinomial.py

+ 20
- 0
regresionpolinomial.py View File

@ -0,0 +1,20 @@
import numpy as np
import matplotlib.pyplot as plt
from sklearn.preprocessing import PolynomialFeatures
from sklearn.linear_model import LinearRegression
###############################
#Datos originales
###############################
m = 100
X = 6 * np.random.rand(m, 1) - 3
y = 0.5 * X**2 + X + 2 + np.random.randn(m, 1)
plt.plot(X,y,".")
poly_features = PolynomialFeatures(degree=2, include_bias=False)
X_poly = poly_features.fit_transform(X)
lin_reg = LinearRegression()
lin_reg.fit(X_poly, y)
yout=lin_reg.predict(X_poly)
plt.plot(X,yout,"*")
plt.show()

Loading…
Cancel
Save