Validation Curve¶

In [2]:

from verticapy.learn.ensemble import RandomForestClassifier
model = RandomForestClassifier(name = "public.RF_titanic")

from verticapy.learn.model_selection import validation_curve
validation_curve(model,
                 "max_depth",
                 [1, 5, 8, 10, 20, 30, 40, 50, 60],
                 input_relation = "public.titanic", 
                 X = ["age", "fare", "parch",],
                 y = "survived", 
                 cv = 3,
                 metric = "auc",)

Out[2]:

	max_depth	training_score_lower	training_score	training_score_upper	test_score_lower	test_score	test_score_upper
1	1	0.6677250045561497	0.6870764806141869	0.7064279566722241	0.6588565762825329	0.6853712353313588	0.7118858943801847
2	5	0.7588933144216624	0.763721392085745	0.7685494697498275	0.6839764916697181	0.6952679573312684	0.7065594229928188
3	8	0.8068505239139409	0.8149642657898739	0.823078007665807	0.6646343970486431	0.6777827129907568	0.6909310289328704
4	10	0.8221340930848655	0.8318132188513967	0.8414923446179279	0.6409136629238706	0.6649657766819059	0.6890178904399412
5	20	0.8341568645426134	0.8446613955791481	0.8551659266156828	0.624672756871346	0.6497515222007944	0.6748302875302427
6	30	0.8240960937055699	0.8395331990957564	0.8549703044859429	0.6390365899321702	0.6672574984315623	0.6954784069309545
7	40	0.8369005892707293	0.8388326636377401	0.8407647380047509	0.6493455161716021	0.6569600913497858	0.6645746665279696
8	50	0.8361307735188002	0.8486359605948212	0.8611411476708422	0.6284083104420073	0.6418611453906484	0.6553139803392896
9	60	0.8401808906816512	0.8436358507795991	0.847090810877547	0.6439477066552249	0.6564913529476023	0.6690349992399797

Rows: 1-9 | Columns: 7