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feature_start_date, feature_end_date should default to min and max dates from all feature tables
reads from config file, does queries in from_objs, and populates values for timechop
label_start_time and label_end_time should default yo min and max dates from labels
model_update_frequency = 100 years
training_as_of_date_frequencies = 100 years
test_as_of_date_frequencies = 100 years
max_training_histories: 100 years
test_durations: 0 days will give a single prediction immediately after training end)
test_label_timespans = training_label_timespan
cohort_conifg:
query: every entity in the data select distinct entity_id from ...
name: all_entities_cohort
add a new parameter for model_grid_preeset that can take one of 5 values - quick (seconds), small (minutes), medium (hours), large (day), xlarge (days)
if we see model_grid defined, then ignore the preset parameter. if nothing is set, then default to quicktrial - give warning
The text was updated successfully, but these errors were encountered:
feature_start_date, feature_end_date should default to min and max dates from all feature tables
label_start_time and label_end_time should default yo min and max dates from labels
model_update_frequency = 100 years
training_as_of_date_frequencies = 100 years
test_as_of_date_frequencies = 100 years
max_training_histories: 100 years
test_durations: 0 days will give a single prediction immediately after training end)
test_label_timespans = training_label_timespan
cohort_conifg:
query: every entity in the data select distinct entity_id from ...
name: all_entities_cohort
label_config:
include_missing_labels_in_train_as: null
name: default = outcome
model_grid_config
add a new parameter for model_grid_preeset that can take one of 5 values - quick (seconds), small (minutes), medium (hours), large (day), xlarge (days)
if we see model_grid defined, then ignore the preset parameter. if nothing is set, then default to quicktrial - give warning
The text was updated successfully, but these errors were encountered: