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initial model

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This commit is contained in:
Michael Duong 2023-10-11 13:23:54 +00:00
parent b570829b5a
commit f4e91162ec
5 changed files with 38 additions and 30 deletions
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2
modules/ml-pipeline/src/pipeline/configs/build_model.yaml
View file

@ -13,6 +13,6 @@ default:
output_filepath: ./data/model/allmodels/
problem_type: regression
eval_metric: mean_squared_error #mean_absolute_error
time_limit: 4000
time_limit: 60
presets: medium_quality
excluded_model_types: ['KNN', 'RF']

6
modules/ml-pipeline/src/pipeline/configs/feature_processor_logic.py
View file

@ -18,6 +18,11 @@ def remove_starting_columns(df):
return df
def keep_negative_carbon_change(df):
df = df[df["CARBON_CHANGE"] < 0]
return df
# def keep_ending_columns(df):
# ending_column_index = [ col_name.endswith("_ENDING") for col_name in list(df.columns)]
# keep_columns = df.columns[ending_column_index].to_list()
@ -27,6 +32,7 @@ def remove_starting_columns(df):
# return df
business_logic = {
"keep_negative_carbon_change": keep_negative_carbon_change
# "remove_starting_columns": remove_starting_columns
# "keep_ENDING_COLUMNS": keep_ending_columns
}

6
modules/ml-pipeline/src/pipeline/configs/post_prediction_logic.py
View file

@ -12,9 +12,11 @@ def clip_predictions_to_minimum_value(
predictions.name = "predictions"
predictions_df = pd.concat([data, predictions], axis=1)
# We expect all prediction to be atleast one point improvement
replace_index = predictions_df["SAP_STARTING"] + 1 > predictions_df["predictions"]
replace_index = (
predictions_df["predictions"] > predictions_df["CARBON_STARTING"] - 1
)
predictions_df.loc[replace_index, "predictions"] = (
predictions_df.loc[replace_index, "SAP_STARTING"] + minimum_value
predictions_df.loc[replace_index, "CARBON_STARTING"] - minimum_value
)
predictions_new = predictions_df["predictions"]

4
modules/ml-pipeline/src/pipeline/configs/settings.yaml
View file

@ -31,9 +31,9 @@ default:
feature_processor_config:
subsample_amount: null
subsample_seed: 0
target: SAP_ENDING
target: CARBON_ENDING
identifier_columns: ["UPRN"]
drop_columns: ["HEAT_DEMAND_CHANGE", "CARBON_CHANGE", "RDSAP_CHANGE", "HEAT_DEMAND_ENDING", "CARBON_ENDING"]
drop_columns: ["HEAT_DEMAND_CHANGE", "CARBON_CHANGE", "RDSAP_CHANGE", "HEAT_DEMAND_ENDING", "SAP_ENDING"]
# retain_features: ["SAP_STARTING", "TOTAL_FLOOR_AREA_DIFF"]
retain_features: null

50
modules/ml-pipeline/src/pipeline/dvc.lock
View file

@ -14,11 +14,11 @@ stages:
- CARBON_CHANGE
- RDSAP_CHANGE
- HEAT_DEMAND_ENDING
- CARBON_ENDING
- SAP_ENDING
default.feature_processor.feature_processor_config.retain_features:
default.feature_processor.feature_processor_config.subsample_amount:
default.feature_processor.feature_processor_config.subsample_seed: 0
default.feature_processor.feature_processor_config.target: SAP_ENDING
default.feature_processor.feature_processor_config.target: CARBON_ENDING
default.feature_processor.feature_processor_type: dataframe
default.prepare_data.data_filepath: s3://retrofit-data-dev/sap_change_model/dataset.parquet
default.prepare_data.input_dataclient_type: aws-s3
@ -29,8 +29,8 @@ stages:
outs:
- path: data/prepared_data/
hash: md5
md5: 9ce5c45722da7fc40491b5a4d00daf9e.dir
size: 33881619
md5: cd9a3d5e6208c1fd5de513b4d5c51b5b.dir
size: 30121189
nfiles: 2
build_model:
cmd: python 2_build_model.py
@ -41,8 +41,8 @@ stages:
size: 5359
- path: data/prepared_data
hash: md5
md5: 9ce5c45722da7fc40491b5a4d00daf9e.dir
size: 33881619
md5: cd9a3d5e6208c1fd5de513b4d5c51b5b.dir
size: 30121189
nfiles: 2
params:
configs/build_model.yaml:
@ -58,7 +58,7 @@ stages:
output_filepath: ./data/model/allmodels/
problem_type: regression
eval_metric: mean_squared_error
time_limit: 4000
time_limit: 60
presets: medium_quality
excluded_model_types:
- KNN
@ -66,13 +66,13 @@ stages:
outs:
- path: data/model/
hash: md5
md5: 7bb5156243b4db39349e80a01ffecde4.dir
size: 473398662
nfiles: 27
md5: 0d43e4ac3985da215dadf5fed8e68200.dir
size: 210841782
nfiles: 21
- path: metrics/fit_metrics.json
hash: md5
md5: 2bb16ac67de8778fbc08171d562b34d5
size: 184
md5: 06f8bb0d004b91c33493dbee9a8763e7
size: 206
generate_predictions:
cmd: python 3_generate_predictions.py
deps:
@ -82,13 +82,13 @@ stages:
size: 3028
- path: data/model
hash: md5
md5: 7bb5156243b4db39349e80a01ffecde4.dir
size: 473398662
nfiles: 27
md5: 0d43e4ac3985da215dadf5fed8e68200.dir
size: 210841782
nfiles: 21
- path: data/prepared_data
hash: md5
md5: 9ce5c45722da7fc40491b5a4d00daf9e.dir
size: 33881619
md5: cd9a3d5e6208c1fd5de513b4d5c51b5b.dir
size: 30121189
nfiles: 2
params:
configs/settings.yaml:
@ -100,8 +100,8 @@ stages:
outs:
- path: data/predictions/
hash: md5
md5: 0bb3cf991906953def81c8204cdcfaf0.dir
size: 374532
md5: acdcb06ee7574672b1148c10c37a868b.dir
size: 275959
nfiles: 1
generate_metrics:
cmd: python 4_generate_metrics.py
@ -112,13 +112,13 @@ stages:
size: 4487
- path: data/predictions
hash: md5
md5: 0bb3cf991906953def81c8204cdcfaf0.dir
size: 374532
md5: acdcb06ee7574672b1148c10c37a868b.dir
size: 275959
nfiles: 1
- path: data/prepared_data
hash: md5
md5: 9ce5c45722da7fc40491b5a4d00daf9e.dir
size: 33881619
md5: cd9a3d5e6208c1fd5de513b4d5c51b5b.dir
size: 30121189
nfiles: 2
params:
configs/settings.yaml:
@ -128,8 +128,8 @@ stages:
outs:
- path: metrics/metrics.json
hash: md5
md5: 2e13ae67759a64261d03224f1c0d4bf4
size: 185
md5: e3bdc173023a7d909704f0313aa1609f
size: 219
startup_cleanup:
cmd: python 0_startup_cleanup.py
deps: