200 observations from a 2 population model. Under population 0, \(x_{1,i}\) has a standard normal distribution, and \(x_{2,i} = (2-x_{1,i}^2+z_i)/3\), where \(z_i\) is also standard normal. Under population 1, \(x_{2,i} = -(2-x_{1,i}^2+z_i)/3\). The optimal classification regions form a checkerboard pattern, with horizontal boundary at \(x_2=0\), vertical boundaries at \(x_1 = \pm \sqrt{2}\).
This is the same model as the cltrain dataset.
data(cltest)Data Frame. Three variables x1, x2 and y. The latter indicates class membership.