Converting Numpy Lstsq residual value to R^2
See http://en.wikipedia.org/wiki/Coefficient_of_determination
Your R2 value =
1 - residual / sum((y - y.mean())**2) which is equivalent to
1 - residual / (n * y.var())As an example:
import numpy as np# Make some data...n = 10x = np.arange(n)y = 3 * x + 5 + np.random.random(n)# Note that polyfit is an easier way to do this...# It would just be "model, resid = np.polyfit(x,y,1,full=True)[:2]" A = np.vstack((x, np.ones(n))).Tmodel, resid = np.linalg.lstsq(A, y)[:2]r2 = 1 - resid / (y.size * y.var())print r2