W3School TIY Editor

import numpy from sklearn.metrics import r2_score numpy.random.seed(2) x = numpy.random.normal(3, 1, 100) y = numpy.random.normal(150, 40, 100) / x train_x = x[:80] train_y = y[:80] test_x = x[80:] test_y = y[80:] mymodel = numpy.poly1d(numpy.polyfit(train_x, train_y, 4)) r2 = r2_score(test_y, mymodel(test_x)) print(r2)