memModel.predict_proba_sql¶

In [ ]:

memModel.predict_proba_sql(X: list)

Returns the SQL code to deploy a classification model.

Parameters¶

Name	Type	Optional	Description
X	list	❌	Names or values of the input predictors.

Returns¶

list : SQL code.

Example¶

In [15]:

from verticapy.learn.memmodel import memModel
model = memModel("BinaryTreeClassifier", {"children_left": [1, 3, None, None, None], 
                                          "children_right": [2, 4, None, None, None],
                                          "feature": [0, 1, None, None, None],
                                          "threshold": ['female', 30, None, None, None],
                                          "value": [None, None, [0.8, 0.1, 0.1], [0.1, 0.8, 0.1], [0.2, 0.2, 0.6]],
                                          "classes": ['a', 'b', 'c',]})
model.predict_proba_sql(['sex', 'fare'])

Out[15]:

["(CASE WHEN sex = 'female' THEN (CASE WHEN fare < '30' THEN 0.1 ELSE 0.2 END) ELSE 0.8 END)",
 "(CASE WHEN sex = 'female' THEN (CASE WHEN fare < '30' THEN 0.8 ELSE 0.2 END) ELSE 0.1 END)",
 "(CASE WHEN sex = 'female' THEN (CASE WHEN fare < '30' THEN 0.1 ELSE 0.6 END) ELSE 0.1 END)"]