Classification Trees Class¶

This is the TPZ.Ctree class in some detail, refer to the source code for mode information and methods.

Module author: Matias Carrasco Kind

class TPZ.Ctree(X, Y, minleaf=4, forest='yes', mstar=2, dict_dim='', impurity='entropy', nclass=array([0, 1]))¶

Creates a classification tree class instance

Parameters:

X (float or int array, 1 row per object) – Preprocessed attributes array (all columns are considered) Y (int array) – Attribute to be predicted minleaf (int, def = 4) – Minimum number of objects on terminal leaf forest (str, ‘yes’/’no’) – Random forest key mstar (int) – Number of random subsample of attributes if forest is used impurity – ‘entropy’/’gini’/’classE’ to compute information gain nclass (int array) – classes array (labels) dict_dim (dict) – dictionary with attributes names

get_branch(line)¶

Same as Rtree.get_branch()

get_vals(line)¶

Same as Rtree.get_vals()

leaves()¶

Same as Rtree.leaves()

leaves_dim()¶

Same as Rtree.leaves_dim()

plot_tree(itn=-1, fileout='TPZ', path='', save_png='no')¶

Same as Rtree.plot_tree()

print_branch(branch)¶

Same as Rtree.print_branch()

save_tree(itn=-1, fileout='TPZ', path='')¶

Same as Rtree.save_tree()