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 Machine Learning Polynomial Regression
Hello All,

I am facing some problem while implementing polynomial regression for my machine learning module. Part of my code is as below:
poly = PolynomialFeatures(degree = 4) 
X_poly = poly.fit_transform(X) 
lin = LinearRegression(), Y)
y_poly_pred = lin.predict(X_poly)
plt.scatter(X['Totalizer'], Y, color='red')
plt.plot(X['Totalizer'], y_poly_pred, color='b')
plt.title('Polynomial Regression')

rmse = np.sqrt(mean_squared_error(Y,y_poly_pred))
r2 = r2_score(Y,y_poly_pred)
Please also see attached picture :

My question is that my predicted values are completely in line with output(label) but still rmse and r2 are respectively 10.2 & 0.99. Why this rmse and r2 are showing in opposite direction that model is not tuned well? Am I missing something important?

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