Ejemplo de regresión polinomial

regresionpolinomial.py

@@ -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()