weka.classifiers.trees.LADTree: : 0,0,0,0,0,0,0,0 | (1)migrat5g = Same_house: -1.285,-1.482,-1.539,0.384,1.878,1.726,0.473,-0.155 | (1)migrat5g != Same_house: 2.072,1.429,0.911,1.102,-1.345,-1.321,-1.406,-1.444 | (2)inctot = 999999: 0.653,0.241,-0.002,0.099,0.158,-0.846,-0.92,0.617 | (2)inctot != 999999: 0.228,-0.063,-0.033,0.024,-0.057,0.16,0.159,-0.42 | (3)ownershg = Owned_or_being_bought_(loan): -0.526,0.018,0.218,0.149,-0.006,0.041,0.036,0.071 | | (5)nmothers = 0: 0.232,-0.194,-0.338,-0.155,-0.373,0.232,1.111,-0.514 | | (5)nmothers != 0: -0.049,-0.095,0.021,0.039,0.256,0.038,-0.421,0.21 | (3)ownershg = Rented: 0.499,0.311,0.105,0.087,0.039,-0.451,-0.385,-0.205 | (4)age = 0: 2.957,-0.517,-0.516,-0.598,-0.592,-0.506,-0.504,0.277 | (4)age != 0: -0.031,0.059,0.033,0.021,-0.004,-0.023,-0.035,-0.02 | | (6)migrat5g = Same_house: -0.245,-0.482,-0.587,0.194,0.295,0.276,0.17,0.379 | | (6)migrat5g != Same_house: 0.249,0.341,0.406,0.364,-0.3,-0.209,-0.395,-0.455 | | (8)migrat5g = Same_state_countydifferent_house: -0.128,0.18,0.304,0.385,0.002,-0.058,-0.313,-0.372 | | (8)migrat5g != Same_state_countydifferent_house: 0.21,-0.042,-0.143,-0.108,0.062,0.006,0.003,0.012 | (7)relateg = Child: 0.023,0.196,0.103,0.118,-0.183,0.017,-0.602,0.327 | | (9)age = 1: 1.998,0.977,-0.567,-0.67,-0.638,-0.57,-0.55,0.019 | | (9)age != 1: 0.119,0.028,0.106,0.058,0.014,-0.033,-0.363,0.071 | (7)relateg != Child: 0.216,0.022,-0.005,0.02,0.092,0.057,0.165,-0.567 Legend: 1, 2, 3, 4, 5, 6, 7, 9 #Tree size (total): 28 #Tree size (number of predictor nodes): 19 #Leaves (number of predictor nodes): 15 #Expanded nodes: 84 #Processed examples: 309343 #Ratio e/n: 3682.654761904762