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Home Page: https://towardsdatascience.com/automated-feature-engineering-in-python-99baf11cc219
Automated feature engineering in Python with Featuretools
Home Page: https://towardsdatascience.com/automated-feature-engineering-in-python-99baf11cc219
features, feature_names = ft.dfs(entityset = es, target_entity = 'clients',
agg_primitives = ['mean', 'max', 'percent_true', 'last'],
trans_primitives = ['years', 'month', 'subtract', 'divide'])
ValueError: ('Unknown transform primitive years. ', 'Call ft.primitives.list_primitives() to get', ' a list of available primitives')
hello,my firend.Recently, I've been studying your featuretools package and I have a question for you. About functions "remove_highly_correlated_features",The documentation says:"We make the assumption that, for a pair of features, the feature that is further right in the feature matrix produced by dfs is the more complex one". I want to know, In the dfs, How to calculate the complexity of the features and then sort them? Why the features on the right are more complex? Thanks
where are your source code??
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