new heat model with new uvalue generation

This commit is contained in:
Michael Duong 2024-10-09 12:56:33 +01:00
parent 343d508cad
commit 7719dd4f84
2 changed files with 26 additions and 25 deletions

View file

@ -19,7 +19,8 @@ default:
input_dataclient_type: aws-s3
output_dataclient_type: local
# data_filepath: s3://retrofit-data-dev/sap_change_model/2024-06-09-10-36-53/dataset_rooms.parquet
data_filepath: s3://retrofit-data-dev/sap_change_model/2024-10-03-22-57-23/dataset_rooms.parquet
# data_filepath: s3://retrofit-data-dev/sap_change_model/2024-10-03-22-57-23/dataset_rooms.parquet
data_filepath: s3://retrofit-data-dev/sap_change_model/2024-10-08-21-58-03/dataset_rooms.parquet
train_proportion: 0.9
output_train_filepath: ./data/prepared_data/train.parquet
output_test_filepath: ./data/prepared_data/test.parquet

View file

@ -46,7 +46,7 @@ stages:
default.feature_processor.feature_processor_config.target: heat_demand_ending
default.feature_processor.feature_processor_type: dataframe
default.prepare_data.data_filepath:
s3://retrofit-data-dev/sap_change_model/2024-10-03-22-57-23/dataset_rooms.parquet
s3://retrofit-data-dev/sap_change_model/2024-10-08-21-58-03/dataset_rooms.parquet
default.prepare_data.input_dataclient_type: aws-s3
default.prepare_data.output_dataclient_type: local
default.prepare_data.output_test_filepath: ./data/prepared_data/test.parquet
@ -55,8 +55,8 @@ stages:
outs:
- path: data/prepared_data/
hash: md5
md5: ac22171e3434233359d3ee05ae82d098.dir
size: 41096450
md5: a2a418c9b72ef168dcc94f8bca824527.dir
size: 41112441
nfiles: 2
build_model:
cmd: python 2_build_model.py
@ -67,8 +67,8 @@ stages:
size: 4820
- path: data/prepared_data
hash: md5
md5: ac22171e3434233359d3ee05ae82d098.dir
size: 41096450
md5: a2a418c9b72ef168dcc94f8bca824527.dir
size: 41112441
nfiles: 2
params:
configs/build_model.yaml:
@ -100,18 +100,18 @@ stages:
outs:
- path: data/fit_predictions/
hash: md5
md5: 58956584afc6939113016c1d252ec199.dir
size: 3126151
md5: a7df97430fe3f5eff6f15cb2d2431e50.dir
size: 3125410
nfiles: 1
- path: data/model/
hash: md5
md5: 68865aace24ff0aa9241ffcec1f465eb.dir
size: 714713875
nfiles: 35
md5: f2dfac63cb8f16cf81ec7f058b38dc26.dir
size: 564562493
nfiles: 36
- path: metrics/fit_metrics.json
hash: md5
md5: 7eb0b3080018ec5a30e2ddc77c3eab91
size: 223
md5: b87b67933d6489d508c4c72f1b543e85
size: 222
generate_predictions:
cmd: python 3_generate_predictions.py
deps:
@ -121,13 +121,13 @@ stages:
size: 2464
- path: data/model
hash: md5
md5: 68865aace24ff0aa9241ffcec1f465eb.dir
size: 714713875
nfiles: 35
md5: f2dfac63cb8f16cf81ec7f058b38dc26.dir
size: 564562493
nfiles: 36
- path: data/prepared_data
hash: md5
md5: ac22171e3434233359d3ee05ae82d098.dir
size: 41096450
md5: a2a418c9b72ef168dcc94f8bca824527.dir
size: 41112441
nfiles: 2
params:
configs/settings.yaml:
@ -139,8 +139,8 @@ stages:
outs:
- path: data/predictions/
hash: md5
md5: 28cc6fbd43a3645ed02fc98ce51a809a.dir
size: 426349
md5: 4def629396860398d224fa175e33d90f.dir
size: 426281
nfiles: 1
generate_metrics:
cmd: python 4_generate_metrics.py
@ -151,13 +151,13 @@ stages:
size: 3447
- path: data/predictions
hash: md5
md5: 28cc6fbd43a3645ed02fc98ce51a809a.dir
size: 426349
md5: 4def629396860398d224fa175e33d90f.dir
size: 426281
nfiles: 1
- path: data/prepared_data
hash: md5
md5: ac22171e3434233359d3ee05ae82d098.dir
size: 41096450
md5: a2a418c9b72ef168dcc94f8bca824527.dir
size: 41112441
nfiles: 2
params:
configs/settings.yaml:
@ -167,7 +167,7 @@ stages:
outs:
- path: metrics/metrics.json
hash: md5
md5: d80f216a55a99847174a7c44c011fe82
md5: 63b75a4ae4c760df62597e7145f87452
size: 223
generate_scenerio_metrics:
cmd: python 5_generate_scenarios.py