Role Class
Some columns play a specific role for specific learners or transforms. This is the complete list.
- Inheritance
-
builtins.objectRole
Examples
from nimbusml import Role
from nimbusml import Pipeline # similar to Pipeline
from nimbusml.linear_model import FastLinearRegressor
import pandas
X = pandas.DataFrame(dict(education=[2,4,6,4,3],
workclass=[0,2,3,4,0],
weights=[1., 1., 1., 2., 1.],
y=[1.1, 2.2, 1.24, 3.4, 3.4]))
lr = FastLinearRegressor() << {Role.Label:'y', Role.Feature:['weights', 'workclass']}
# equivalent to
# FastLinearRegressor(label = 'y',
feature = ['weights', 'workclass'])
exp = Pipeline([lr])
exp.fit(X)
prediction = exp.predict(X)
Remarks
Column roles can be specified for each transform and learner during initialization. For more details, please refer to Roles.
Methods
to_attribute |
Converts a role into an attribute name.
|
to_parameter |
Converts a role into (as per manifesrt.json) parameter name.
|
to_role |
Converts an attribute name to role
|
to_attribute
Converts a role into an attribute name.
GroupId --> row_group_column_name
.
to_attribute(role, suffix='_column_name')
Parameters
Name | Description |
---|---|
role
Required
|
|
suffix
|
Default value: _column_name
|
to_parameter
Converts a role into (as per manifesrt.json) parameter name.
GroupId --> RowGroupColumnName
.
to_parameter(role, suffix='ColumnName')
Parameters
Name | Description |
---|---|
role
Required
|
|
suffix
|
Default value: ColumnName
|
to_role
Converts an attribute name to role
row_group_column_name -> group_id
.
to_role(column_name, suffix='_column_name')
Parameters
Name | Description |
---|---|
column_name
Required
|
|
suffix
|
Default value: _column_name
|
Attributes
Feature
Feature = 'Feature'
GroupId
GroupId = 'GroupId'
Item
Item = 'Item'
Label
Label = 'Label'
Name
Name = 'Name'
RowId
RowId = 'RowId'
User
User = 'User'
Weight
Weight = 'Weight'