TSFresh primitives for featuretools
Project description
Featuretools TSFresh Primitives
Installation
pip install 'featuretools[tsfresh]'
Calculating Features
In tsfresh
, this is how to calculate a feature.
from tsfresh.feature_extraction.feature_calculators import agg_autocorrelation
data = list(range(10))
param = [{'f_agg': 'mean', 'maxlag': 5}]
agg_autocorrelation(data, param=param)
[('f_agg_"mean"__maxlag_5', 0.1717171717171717)]
With tsfresh primtives in featuretools
, this is how to calculate the same feature.
from featuretools.tsfresh import AggAutocorrelation
data = list(range(10))
AggAutocorrelation(f_agg='mean', maxlag=5)(data)
0.1717171717171717
Combining Primitives
In featuretools
, this is how to combine tsfresh primitives with built-in or other installed primitives.
import featuretools as ft
from featuretools.tsfresh import AggAutocorrelation, Mean
entityset = ft.demo.load_mock_customer(return_entityset=True)
agg_primitives = [Mean, AggAutocorrelation(f_agg='mean', maxlag=5)]
feature_matrix, features = ft.dfs(entityset=entityset, target_entity='sessions', agg_primitives=agg_primitives)
feature_matrix[[
'MEAN(transactions.amount)',
'AGG_AUTOCORRELATION(transactions.amount, f_agg=mean, maxlag=5)',
]].head()
MEAN(transactions.amount) AGG_AUTOCORRELATION(transactions.amount, f_agg=mean, maxlag=5)
session_id
1 76.813125 0.044268
2 74.696000 -0.053110
3 88.600000 0.007520
4 64.557200 -0.034542
5 70.638182 -0.100571
Notice that tsfresh primtives are applied across relationships in an entityset generating many features that are otherwise not possible.
feature_matrix[['customers.AGG_AUTOCORRELATION(transactions.amount, f_agg=mean, maxlag=5)']].head()
customers.AGG_AUTOCORRELATION(transactions.amount, f_agg=mean, maxlag=5)
session_id
1 0.011102
2 -0.001686
3 -0.010679
4 0.011204
5 -0.010679
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Close
Hashes for featuretools_tsfresh_primitives-0.4.0.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | dc7553eb2a49842fac248a7c0bc2d148eaf4ae066878c0e03d60de96b8a473fe |
|
MD5 | 75635c778e52162abf51b36f57d71e6e |
|
BLAKE2b-256 | 1cdf2fd3d9c930b20256a17e11ef72167d6af9153c994f31452265ee7acb7a0b |
Close
Hashes for featuretools_tsfresh_primitives-0.4.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 626609a08b02459466dfa1345e4bf67f65ad0873ac80e2823fcc1c78eb99706f |
|
MD5 | c73dd50518e050aad50e1b318615ac83 |
|
BLAKE2b-256 | fb1b3d4b3ffb73ef4c493d180345c9916c169aadda962b196bb7ab9614446324 |