Training dataset for classification
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 √{2}.
This is the same model as the cltest dataset.
data(cltrain)
Data Frame. Three variables x1, x2 and y. The latter indicates class membership.
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