Using featuretool, how to use dfs primitives individually?

Question

Could you help me? when I used feturestools, I use iris dataset, it has 4 features as follows: f1, f2, f3, f4, when I use ft.dfsI have 3 tow questions. 1. I found that feature_matrix has too much features. the 'divide_by_feature' and 'modulo_numeric' didn't act on original features individually. It firstly act divide_by_feature' then got 4 features newly, and then act 'modulo_numeric' on original features and new features. I hope the two primitives can act on original features individually. How should I do? 2. I use transform primitives like trans_primitives = ['subtract_numeric_scalar', 'modulo_numeric']. I found that subtract_numeric_scalar can pass an value, however, I don't know how to pass? 3. I wonder how to use all transform primitives? default, trans_primitives=None, by now, I can solve it like this: trans_primitives = ['is_null','diff',...], however, I think that it's trouble.

could you give me some advice? Thank you!

enter image description here

Jeff Hernandez · Accepted Answer · 2020-02-10T17:34:38.200

You can use max_depth to control the complexity of the features. When max_depth=1, the primitives will use only original features.

features = ft.dfs(
    entityset=es,
    target_entity='data',
    trans_primitives=['divide_by_feature', 'modulo_numeric'],
    features_only=True,
    max_depth=1,
)

[<Feature: f1>,
<Feature: f2>,
<Feature: f3>,
<Feature: f4>,
<Feature: 1 / f3>,
<Feature: 1 / f1>,
<Feature: 1 / f2>,
<Feature: 1 / f4>,
<Feature: f1 % f2>,
<Feature: f4 % f3>,
<Feature: f4 % f2>,
<Feature: f1 % f3>,
<Feature: f2 % f4>,
<Feature: f4 % f1>,
<Feature: f3 % f2>,
<Feature: f3 % f1>,
<Feature: f2 % f1>,
<Feature: f3 % f4>,
<Feature: f2 % f3>,
<Feature: f1 % f4>]

You can create an instance of a primitive with the parameters. This is how you can pass a value to subtract_numeric_scalar.

from featuretools.primitives import SubtractNumericScalar

ft.dfs(
    ...
    trans_primitives=[SubtractNumericScalar(value=2)]
)

You can use all transform primitives by extracting the names from the primitive list.

primitives = ft.list_primitives()
primitives = primitives.groupby('type')
transforms = primitives.get_group('transform')
transforms = transforms.name.values.tolist()

['less_than_scalar',
'divide_numeric',
'latitude',
'add_numeric',
'week',
'greater_than_equal_to_scalar',
'and',
'multiply_numeric_scalar',
'not',
'second',
'greater_than_scalar',
'modulo_numeric_scalar',
'scalar_subtract_numeric_feature',
'diff',
'day',
'cum_min',
'divide_by_feature',
'less_than_equal_to',
'time_since',
'time_since_previous',
'cum_count',
'year',
'is_null',
'num_characters',
'equal_scalar',
'is_weekend',
'less_than_equal_to_scalar',
'longitude',
'add_numeric_scalar',
'month',
'less_than',
'or',
'multiply_boolean',
'percentile',
'minute',
'not_equal_scalar',
'greater_than_equal_to',
'modulo_by_feature',
'multiply_numeric',
'negate',
'hour',
'cum_max',
'greater_than',
'modulo_numeric',
'subtract_numeric_scalar',
'isin',
'cum_mean',
'divide_numeric_scalar',
'num_words',
'absolute',
'cum_sum',
'not_equal',
'weekday',
'equal',
'haversine',
'subtract_numeric']

Let me know if this helps.

Using featuretool, how to use dfs primitives individually?

1 Answers1