我希望功能工具根据我在实体集中声明的时间索引和截止时间创建功能。
我有一个包含时间变量以及数值和分类变量的数据集。有一个ITEMID 列,每个ITEMID 有2 到12 行数据。
使用开始日期和交易日期等列,各种数字和分类列。给定 ITEMID 的所有行的开始日期相同,而每行的交易日期不同。
这是实体集的代码
# creating and entity set
entity_set = ft.EntitySet(id = 'rem_dur')
# adding a dataframe
entity_set.entity_from_dataframe(entity_id = 'enh', dataframe = dataset, index = 'unique_id'
,,variable_types = {'Start_Date': ft.variable_types.DatetimeTimeIndex}))
#unique_id is just row number from 1 to number of rows in dataset
entity_set.normalize_entity(base_entity_id='enh', new_entity_id= 'categorical_vars', index = 'ITEMID',
additional_variables = ['cat_var_1', 'cat_var_2'])
###cutoff date
cutoff_df = dataset[["unique_id", "trans_date"]]
cutoff_df["trans_date"] = pd.to_datetime(cutoff_df["trans_date"])
##feature engg
feature_matrix_2, feature_names_2 = ft.dfs(entityset=entity_set
,target_entity = 'enh'
,max_depth = 2
,verbose = 1
,ignore_entities = ['categorical_vars']
,ignore_variables =ignore_features_dict
,dask_kwargs={'cluster': cluster}
,cutoff_time=cutoff_df
,cutoff_time_in_index=False
)
It's unable to generate any time series features. It's returning just all the features except the ones which are ignored.