Model.fit¶

In [ ]:

Model.fit(input_relation: (str, vDataFrame), 
          X: list = [], 
          key_columns: list = [], 
          index: str = "")

Trains the model.

Parameters¶

Name	Type	Optional	Description
input_relation	str / vDataFrame	❌	Training relation.
X	list	✓	List of the predictors. If empty, all the numerical vcolumns will be used.
key_columns	list	✓	Columns not used during the algorithm computation but which will be used to create the final relation.
index	str	✓	Index to use to identify each row separately. It is highly recommanded to have one already in the main table to avoid creation of temporary tables.

Returns¶

object : self

Example¶

In [5]:

from verticapy.learn.cluster import DBSCAN
model = DBSCAN(name = "public.DBSCAN_iris")
model.fit("public.iris", 
          ["PetalLengthCm", "PetalWidthCm"])

Out[5]:

=======
details
=======
Number of Clusters: 6
Number of Outliers: 0

===============
Additional Info
===============
Input Relation : public.iris
X : "PetalLengthCm", "PetalWidthCm"