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use test dataset
This commit is contained in:
parent
a60a3bd285
commit
790c3a9456
3 changed files with 23 additions and 23 deletions
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@ -13,6 +13,6 @@ default:
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output_filepath: ./data/model/allmodels/
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problem_type: regression
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eval_metric: mean_squared_error #mean_absolute_error
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time_limit: 180
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time_limit: 4000
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presets: medium_quality
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excluded_model_types: ['KNN', 'RF']
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@ -21,7 +21,7 @@ default:
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# data_filepath: s3://retrofit-data-dev/sap_change_model/dataset_with_differencing.parquet
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# data_filepath: s3://retrofit-data-dev/sap_change_model/floor_area_clean_test.parquet
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# data_filepath: s3://retrofit-data-dev/sap_change_model/dataset_without_differencing.parquet
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data_filepath: s3://retrofit-data-dev/sap_change_model/dataset.parquet
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data_filepath: s3://retrofit-data-dev/sap_change_model/dataset_test.parquet
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train_proportion: 0.9
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output_train_filepath: ./data/prepared_data/train.parquet
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output_test_filepath: ./data/prepared_data/test.parquet
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@ -20,7 +20,7 @@ stages:
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default.feature_processor.feature_processor_config.subsample_seed: 0
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default.feature_processor.feature_processor_config.target: SAP_ENDING
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default.feature_processor.feature_processor_type: dataframe
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default.prepare_data.data_filepath: s3://retrofit-data-dev/sap_change_model/dataset.parquet
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default.prepare_data.data_filepath: s3://retrofit-data-dev/sap_change_model/dataset_test.parquet
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default.prepare_data.input_dataclient_type: aws-s3
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default.prepare_data.output_dataclient_type: local
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default.prepare_data.output_test_filepath: ./data/prepared_data/test.parquet
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@ -29,8 +29,8 @@ stages:
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outs:
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- path: data/prepared_data/
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hash: md5
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md5: 9ce5c45722da7fc40491b5a4d00daf9e.dir
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size: 33881619
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md5: cd75be9fecff0c647792dd2db648085c.dir
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size: 37056053
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nfiles: 2
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build_model:
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cmd: python 2_build_model.py
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@ -41,8 +41,8 @@ stages:
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size: 5359
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- path: data/prepared_data
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hash: md5
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md5: 9ce5c45722da7fc40491b5a4d00daf9e.dir
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size: 33881619
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md5: cd75be9fecff0c647792dd2db648085c.dir
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size: 37056053
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nfiles: 2
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params:
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configs/build_model.yaml:
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@ -66,13 +66,13 @@ stages:
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outs:
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- path: data/model/
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hash: md5
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md5: 7bb5156243b4db39349e80a01ffecde4.dir
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size: 473398662
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md5: 7a5527f779efcb1a7db068148b6bcc45.dir
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size: 422448184
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nfiles: 27
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- path: metrics/fit_metrics.json
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hash: md5
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md5: 2bb16ac67de8778fbc08171d562b34d5
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size: 184
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md5: 77790bb9485c04c77125e361921c3774
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size: 225
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generate_predictions:
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cmd: python 3_generate_predictions.py
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deps:
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@ -82,13 +82,13 @@ stages:
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size: 3028
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- path: data/model
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hash: md5
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md5: 7bb5156243b4db39349e80a01ffecde4.dir
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size: 473398662
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md5: 7a5527f779efcb1a7db068148b6bcc45.dir
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size: 422448184
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nfiles: 27
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- path: data/prepared_data
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hash: md5
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md5: 9ce5c45722da7fc40491b5a4d00daf9e.dir
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size: 33881619
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md5: cd75be9fecff0c647792dd2db648085c.dir
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size: 37056053
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nfiles: 2
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params:
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configs/settings.yaml:
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@ -100,8 +100,8 @@ stages:
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outs:
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- path: data/predictions/
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hash: md5
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md5: 0bb3cf991906953def81c8204cdcfaf0.dir
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size: 374532
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md5: 28d2876e6c6d5cc64844ecc1d6ac40b2.dir
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size: 346687
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nfiles: 1
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generate_metrics:
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cmd: python 4_generate_metrics.py
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@ -112,13 +112,13 @@ stages:
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size: 4487
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- path: data/predictions
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hash: md5
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md5: 0bb3cf991906953def81c8204cdcfaf0.dir
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size: 374532
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md5: 28d2876e6c6d5cc64844ecc1d6ac40b2.dir
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size: 346687
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nfiles: 1
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- path: data/prepared_data
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hash: md5
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md5: 9ce5c45722da7fc40491b5a4d00daf9e.dir
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size: 33881619
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md5: cd75be9fecff0c647792dd2db648085c.dir
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size: 37056053
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nfiles: 2
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params:
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configs/settings.yaml:
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@ -128,8 +128,8 @@ stages:
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outs:
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- path: metrics/metrics.json
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hash: md5
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md5: 2e13ae67759a64261d03224f1c0d4bf4
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size: 185
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md5: 7afd04d656dc83ad6aa942d9c63f5b4e
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size: 224
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startup_cleanup:
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cmd: python 0_startup_cleanup.py
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deps:
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