Model.decision_function¶

In [ ]:

Model.decision_function(vdf: Union[str, vDataFrame],
                        X: list = [],
                        name: str = "",
                        inplace: bool = True)

Returns the anomaly score using the input relation.

Parameters¶

Name	Type	Optional	Description
vdf	str / vDataFrame	❌	Object to use to run the prediction. It can also be a customized relation but you need to englobe it using an alias. For example "(SELECT 1) x" is correct whereas "(SELECT 1)" or "SELECT 1" are incorrect.
X	list	✓	List of the columns used to deploy the models. If empty, the model predictors will be used.
name	str	✓	Name of the added vcolumn. If empty, a name will be generated.
inplace	bool	✓	If set to True, the prediction will be added to the vDataFrame.

Returns¶

vDataFrame : the input object.

Example¶

In [20]:

from verticapy import vDataFrame
iris = vDataFrame("public.iris")
display(iris)

	123 SepalLengthCm Numeric(5,2)	123 SepalWidthCm Numeric(5,2)	123 PetalLengthCm Numeric(5,2)	123 PetalWidthCm Numeric(5,2)	Abc Species Varchar(30)
1	4.3	3.0	1.1	0.1	Iris-setosa
2	4.4	2.9	1.4	0.2	Iris-setosa
3	4.4	3.0	1.3	0.2	Iris-setosa
4	4.4	3.2	1.3	0.2	Iris-setosa
5	4.5	2.3	1.3	0.3	Iris-setosa
6	4.6	3.1	1.5	0.2	Iris-setosa
7	4.6	3.2	1.4	0.2	Iris-setosa
8	4.6	3.4	1.4	0.3	Iris-setosa
9	4.6	3.6	1.0	0.2	Iris-setosa
10	4.7	3.2	1.3	0.2	Iris-setosa
11	4.7	3.2	1.6	0.2	Iris-setosa
12	4.8	3.0	1.4	0.1	Iris-setosa
13	4.8	3.0	1.4	0.3	Iris-setosa
14	4.8	3.1	1.6	0.2	Iris-setosa
15	4.8	3.4	1.6	0.2	Iris-setosa
16	4.8	3.4	1.9	0.2	Iris-setosa
17	4.9	2.4	3.3	1.0	Iris-versicolor
18	4.9	2.5	4.5	1.7	Iris-virginica
19	4.9	3.0	1.4	0.2	Iris-setosa
20	4.9	3.1	1.5	0.1	Iris-setosa
21	4.9	3.1	1.5	0.1	Iris-setosa
22	4.9	3.1	1.5	0.1	Iris-setosa
23	5.0	2.0	3.5	1.0	Iris-versicolor
24	5.0	2.3	3.3	1.0	Iris-versicolor
25	5.0	3.0	1.6	0.2	Iris-setosa
26	5.0	3.2	1.2	0.2	Iris-setosa
27	5.0	3.3	1.4	0.2	Iris-setosa
28	5.0	3.4	1.5	0.2	Iris-setosa
29	5.0	3.4	1.6	0.4	Iris-setosa
30	5.0	3.5	1.3	0.3	Iris-setosa
31	5.0	3.5	1.6	0.6	Iris-setosa
32	5.0	3.6	1.4	0.2	Iris-setosa
33	5.1	2.5	3.0	1.1	Iris-versicolor
34	5.1	3.3	1.7	0.5	Iris-setosa
35	5.1	3.4	1.5	0.2	Iris-setosa
36	5.1	3.5	1.4	0.2	Iris-setosa
37	5.1	3.5	1.4	0.3	Iris-setosa
38	5.1	3.7	1.5	0.4	Iris-setosa
39	5.1	3.8	1.5	0.3	Iris-setosa
40	5.1	3.8	1.6	0.2	Iris-setosa
41	5.1	3.8	1.9	0.4	Iris-setosa
42	5.2	2.7	3.9	1.4	Iris-versicolor
43	5.2	3.4	1.4	0.2	Iris-setosa
44	5.2	3.5	1.5	0.2	Iris-setosa
45	5.2	4.1	1.5	0.1	Iris-setosa
46	5.3	3.7	1.5	0.2	Iris-setosa
47	5.4	3.0	4.5	1.5	Iris-versicolor
48	5.4	3.4	1.5	0.4	Iris-setosa
49	5.4	3.4	1.7	0.2	Iris-setosa
50	5.4	3.7	1.5	0.2	Iris-setosa
51	5.4	3.9	1.3	0.4	Iris-setosa
52	5.4	3.9	1.7	0.4	Iris-setosa
53	5.5	2.3	4.0	1.3	Iris-versicolor
54	5.5	2.4	3.7	1.0	Iris-versicolor
55	5.5	2.4	3.8	1.1	Iris-versicolor
56	5.5	2.5	4.0	1.3	Iris-versicolor
57	5.5	2.6	4.4	1.2	Iris-versicolor
58	5.5	3.5	1.3	0.2	Iris-setosa
59	5.5	4.2	1.4	0.2	Iris-setosa
60	5.6	2.5	3.9	1.1	Iris-versicolor
61	5.6	2.7	4.2	1.3	Iris-versicolor
62	5.6	2.8	4.9	2.0	Iris-virginica
63	5.6	2.9	3.6	1.3	Iris-versicolor
64	5.6	3.0	4.1	1.3	Iris-versicolor
65	5.6	3.0	4.5	1.5	Iris-versicolor
66	5.7	2.5	5.0	2.0	Iris-virginica
67	5.7	2.6	3.5	1.0	Iris-versicolor
68	5.7	2.8	4.1	1.3	Iris-versicolor
69	5.7	2.8	4.5	1.3	Iris-versicolor
70	5.7	2.9	4.2	1.3	Iris-versicolor
71	5.7	3.0	4.2	1.2	Iris-versicolor
72	5.7	3.8	1.7	0.3	Iris-setosa
73	5.7	4.4	1.5	0.4	Iris-setosa
74	5.8	2.6	4.0	1.2	Iris-versicolor
75	5.8	2.7	3.9	1.2	Iris-versicolor
76	5.8	2.7	4.1	1.0	Iris-versicolor
77	5.8	2.7	5.1	1.9	Iris-virginica
78	5.8	2.7	5.1	1.9	Iris-virginica
79	5.8	2.8	5.1	2.4	Iris-virginica
80	5.8	4.0	1.2	0.2	Iris-setosa
81	5.9	3.0	4.2	1.5	Iris-versicolor
82	5.9	3.0	5.1	1.8	Iris-virginica
83	5.9	3.2	4.8	1.8	Iris-versicolor
84	6.0	2.2	4.0	1.0	Iris-versicolor
85	6.0	2.2	5.0	1.5	Iris-virginica
86	6.0	2.7	5.1	1.6	Iris-versicolor
87	6.0	2.9	4.5	1.5	Iris-versicolor
88	6.0	3.0	4.8	1.8	Iris-virginica
89	6.0	3.4	4.5	1.6	Iris-versicolor
90	6.1	2.6	5.6	1.4	Iris-virginica
91	6.1	2.8	4.0	1.3	Iris-versicolor
92	6.1	2.8	4.7	1.2	Iris-versicolor
93	6.1	2.9	4.7	1.4	Iris-versicolor
94	6.1	3.0	4.6	1.4	Iris-versicolor
95	6.1	3.0	4.9	1.8	Iris-virginica
96	6.2	2.2	4.5	1.5	Iris-versicolor
97	6.2	2.8	4.8	1.8	Iris-virginica
98	6.2	2.9	4.3	1.3	Iris-versicolor
99	6.2	3.4	5.4	2.3	Iris-virginica
100	6.3	2.3	4.4	1.3	Iris-versicolor

Rows: 1-100 | Columns: 5

In [21]:

from verticapy.learn.ensemble import IsolationForest
model = IsolationForest(name = "public.iforest_iris",)
model.fit("public.iris", ["PetalLengthCm", "PetalWidthCm"],)
model.decision_function(iris, 
                        X = ["PetalLengthCm", "PetalWidthCm"],
                        name = "anomaly_score")

Out[21]:

	123 SepalLengthCm Numeric(5,2)	123 SepalWidthCm Numeric(5,2)	123 PetalLengthCm Numeric(5,2)	123 PetalWidthCm Numeric(5,2)	Abc Species Varchar(30)	123 anomaly_score Float
1	4.3	3.0	1.1	0.1	Iris-setosa	0.659739042585392
2	4.4	2.9	1.4	0.2	Iris-setosa	0.420082971583312
3	4.4	3.0	1.3	0.2	Iris-setosa	0.498423387382426
4	4.4	3.2	1.3	0.2	Iris-setosa	0.498423387382426
5	4.5	2.3	1.3	0.3	Iris-setosa	0.556997197155483
6	4.6	3.1	1.5	0.2	Iris-setosa	0.420082971583312
7	4.6	3.2	1.4	0.2	Iris-setosa	0.420082971583312
8	4.6	3.4	1.4	0.3	Iris-setosa	0.49887795203249
9	4.6	3.6	1.0	0.2	Iris-setosa	0.599654772295689
10	4.7	3.2	1.3	0.2	Iris-setosa	0.498423387382426
11	4.7	3.2	1.6	0.2	Iris-setosa	0.503942694083102
12	4.8	3.0	1.4	0.1	Iris-setosa	0.52687454418251
13	4.8	3.0	1.4	0.3	Iris-setosa	0.49887795203249
14	4.8	3.1	1.6	0.2	Iris-setosa	0.503942694083102
15	4.8	3.4	1.6	0.2	Iris-setosa	0.503942694083102
16	4.8	3.4	1.9	0.2	Iris-setosa	0.572369018409518
17	4.9	2.4	3.3	1.0	Iris-versicolor	0.550781575723598
18	4.9	2.5	4.5	1.7	Iris-virginica	0.51874411584425
19	4.9	3.0	1.4	0.2	Iris-setosa	0.420082971583312
20	4.9	3.1	1.5	0.1	Iris-setosa	0.52687454418251
21	4.9	3.1	1.5	0.1	Iris-setosa	0.52687454418251
22	4.9	3.1	1.5	0.1	Iris-setosa	0.52687454418251
23	5.0	2.0	3.5	1.0	Iris-versicolor	0.540035498982027
24	5.0	2.3	3.3	1.0	Iris-versicolor	0.550781575723598
25	5.0	3.0	1.6	0.2	Iris-setosa	0.503942694083102
26	5.0	3.2	1.2	0.2	Iris-setosa	0.498423387382426
27	5.0	3.3	1.4	0.2	Iris-setosa	0.420082971583312
28	5.0	3.4	1.5	0.2	Iris-setosa	0.420082971583312
29	5.0	3.4	1.6	0.4	Iris-setosa	0.550667762747082
30	5.0	3.5	1.3	0.3	Iris-setosa	0.556997197155483
31	5.0	3.5	1.6	0.6	Iris-setosa	0.621158118240602
32	5.0	3.6	1.4	0.2	Iris-setosa	0.420082971583312
33	5.1	2.5	3.0	1.1	Iris-versicolor	0.607170190929157
34	5.1	3.3	1.7	0.5	Iris-setosa	0.592505242613475
35	5.1	3.4	1.5	0.2	Iris-setosa	0.420082971583312
36	5.1	3.5	1.4	0.2	Iris-setosa	0.420082971583312
37	5.1	3.5	1.4	0.3	Iris-setosa	0.49887795203249
38	5.1	3.7	1.5	0.4	Iris-setosa	0.546585798648008
39	5.1	3.8	1.5	0.3	Iris-setosa	0.49887795203249
40	5.1	3.8	1.6	0.2	Iris-setosa	0.503942694083102
41	5.1	3.8	1.9	0.4	Iris-setosa	0.609710102509021
42	5.2	2.7	3.9	1.4	Iris-versicolor	0.516274974136911
43	5.2	3.4	1.4	0.2	Iris-setosa	0.420082971583312
44	5.2	3.5	1.5	0.2	Iris-setosa	0.420082971583312
45	5.2	4.1	1.5	0.1	Iris-setosa	0.52687454418251
46	5.3	3.7	1.5	0.2	Iris-setosa	0.420082971583312
47	5.4	3.0	4.5	1.5	Iris-versicolor	0.419805091210644
48	5.4	3.4	1.5	0.4	Iris-setosa	0.546585798648008
49	5.4	3.4	1.7	0.2	Iris-setosa	0.503942694083102
50	5.4	3.7	1.5	0.2	Iris-setosa	0.420082971583312
51	5.4	3.9	1.3	0.4	Iris-setosa	0.59795159480585
52	5.4	3.9	1.7	0.4	Iris-setosa	0.550667762747082
53	5.5	2.3	4.0	1.3	Iris-versicolor	0.449698347181578
54	5.5	2.4	3.7	1.0	Iris-versicolor	0.528429897740535
55	5.5	2.4	3.8	1.1	Iris-versicolor	0.522724248035921
56	5.5	2.5	4.0	1.3	Iris-versicolor	0.449698347181578
57	5.5	2.6	4.4	1.2	Iris-versicolor	0.514087951901546
58	5.5	3.5	1.3	0.2	Iris-setosa	0.498423387382426
59	5.5	4.2	1.4	0.2	Iris-setosa	0.420082971583312
60	5.6	2.5	3.9	1.1	Iris-versicolor	0.522724248035921
61	5.6	2.7	4.2	1.3	Iris-versicolor	0.437068329139587
62	5.6	2.8	4.9	2.0	Iris-virginica	0.492799360096466
63	5.6	2.9	3.6	1.3	Iris-versicolor	0.53587036832664
64	5.6	3.0	4.1	1.3	Iris-versicolor	0.449698347181578
65	5.6	3.0	4.5	1.5	Iris-versicolor	0.419805091210644
66	5.7	2.5	5.0	2.0	Iris-virginica	0.492799360096466
67	5.7	2.6	3.5	1.0	Iris-versicolor	0.540035498982027
68	5.7	2.8	4.1	1.3	Iris-versicolor	0.449698347181578
69	5.7	2.8	4.5	1.3	Iris-versicolor	0.438825555170071
70	5.7	2.9	4.2	1.3	Iris-versicolor	0.437068329139587
71	5.7	3.0	4.2	1.2	Iris-versicolor	0.504220225794528
72	5.7	3.8	1.7	0.3	Iris-setosa	0.556932032694213
73	5.7	4.4	1.5	0.4	Iris-setosa	0.546585798648008
74	5.8	2.6	4.0	1.2	Iris-versicolor	0.507699540508442
75	5.8	2.7	3.9	1.2	Iris-versicolor	0.521411835838751
76	5.8	2.7	4.1	1.0	Iris-versicolor	0.526259903074188
77	5.8	2.7	5.1	1.9	Iris-virginica	0.47399267499135
78	5.8	2.7	5.1	1.9	Iris-virginica	0.47399267499135
79	5.8	2.8	5.1	2.4	Iris-virginica	0.602390814046936
80	5.8	4.0	1.2	0.2	Iris-setosa	0.498423387382426
81	5.9	3.0	4.2	1.5	Iris-versicolor	0.467431467760989
82	5.9	3.0	5.1	1.8	Iris-virginica	0.458499620384559
83	5.9	3.2	4.8	1.8	Iris-versicolor	0.473770225846824
84	6.0	2.2	4.0	1.0	Iris-versicolor	0.526259903074188
85	6.0	2.2	5.0	1.5	Iris-virginica	0.455499899522817
86	6.0	2.7	5.1	1.6	Iris-versicolor	0.508263558185156
87	6.0	2.9	4.5	1.5	Iris-versicolor	0.419805091210644
88	6.0	3.0	4.8	1.8	Iris-virginica	0.473770225846824
89	6.0	3.4	4.5	1.6	Iris-versicolor	0.501536055452885
90	6.1	2.6	5.6	1.4	Iris-virginica	0.552300722878815
91	6.1	2.8	4.0	1.3	Iris-versicolor	0.449698347181578
92	6.1	2.8	4.7	1.2	Iris-versicolor	0.539779080881098
93	6.1	2.9	4.7	1.4	Iris-versicolor	0.440970450049708
94	6.1	3.0	4.6	1.4	Iris-versicolor	0.455130791015483
95	6.1	3.0	4.9	1.8	Iris-virginica	0.44461362142099
96	6.2	2.2	4.5	1.5	Iris-versicolor	0.419805091210644
97	6.2	2.8	4.8	1.8	Iris-virginica	0.473770225846824
98	6.2	2.9	4.3	1.3	Iris-versicolor	0.437068329139587
99	6.2	3.4	5.4	2.3	Iris-virginica	0.543576868934472
100	6.3	2.3	4.4	1.3	Iris-versicolor	0.438825555170071

Rows: 1-100 | Columns: 6