bf6474b0fac4435737ca8a2afe83209df2e3a980,mlxtend/evaluate/decision_regions.py,,plot_decision_regions,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,15

Before Change

    // make color map
    n_classes = np.unique(y).shape[0]
    colors = colors.split(",")
    cmap = ListedColormap(colors[:n_classes])

    // plot the decision surface
    if dim == "2d":

After Change

    n_classes = np.unique(y).shape[0]
    colors = colors.split(",")
    colors_gen = cycle(colors)
    colors = [next(colors_gen) for c in range(n_classes)]

    if dim == "2d":
        y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1

Instances