junte/ML
1
0
Fork 0
mirror of https://github.com/Hestia-Homes/ML.git synced 2026-06-08 11:17:25 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

dvc push

Browse source
This commit is contained in:
Khalim Conn-Kowlessar 2024-08-02 15:27:51 +01:00
parent 119ce13740
commit 5f73c4ab3b
2 changed files with 38 additions and 74 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

53
modules/ml-pipeline/src/pipeline/configs/settings.yaml
View file

@ -38,13 +38,8 @@ default:
identifier_columns: ["uprn"]
# drop_columns: ["heat_demand_change", "carbon_change", "rdsap_change", "heat_demand_ending", "carbon_ending", "days_to_starting", "days_to_ending"]
drop_columns: ["hot_water_kwh"]
# [
# "sap_ending", "heat_demand_change", "carbon_change", "rdsap_change", "heat_demand_ending", "carbon_ending",
# "heating_cost_ending", "hot_water_cost_ending",
# # "days_to_starting", "days_to_ending",
# 'number_habitable_rooms_starting', 'number_habitable_rooms_ending', 'number_heated_rooms_starting', 'number_heated_rooms_ending',
# 'number_habitable_rooms', 'number_heated_rooms']
retain_features: ['uprn', 'heating-cost-current',
retain_features: [
'uprn', 'heating-cost-current',
'co2-emissions-current',
'hot-water-cost-current',
'total-floor-area',
@ -68,7 +63,7 @@ default:
'energy-consumption-current',
'construction-age-band',
'hotwater-description',
'lodgement-datetime',
# 'lodgement-datetime',
'main-fuel',
'hot-water-energy-eff',
'co2-emiss-curr-per-floor-area',
@ -78,60 +73,38 @@ default:
'extension-count',
'number-open-fireplaces',
'number-heated-rooms',
'lodgement-date',
# 'lodgement-date',
# 'number-habitable-rooms',
'windows-description',
'local-authority',
# 'local-authority',
'photo-supply',
'heat-loss-corridor',
'posttown',
# 'posttown',
# 'address',
'flat-top-storey',
'unheated-corridor-length',
'fixed-lighting-outlets-count',
'inspection-date',
# 'inspection-date',
'tenure',
'county',
'constituency-label',
# 'county',
# 'constituency-label',
'multi-glaze-proportion',
'solar-water-heating-flag',
# 'address2',
'energy-tariff',
'floor-height',
'constituency',
'uprn-source',
# 'uprn-source',
'transaction-type',
'floor-energy-eff',
'postcode',
# 'postcode',
'lodgement-month',
'lighting-cost-current',
'glazed-area',
# 'address1',
'floor-env-eff',
'main-heating-controls']
# retain_features: ['uprn', 'sap_starting', 'hot_water_energy_eff_ending',
# 'mainheat_energy_eff_ending', 'constituency', 'roof_energy_eff_ending',
# 'walls_energy_eff_ending', 'secondheat_description_ending',
# 'property_type', 'mainheatc_energy_eff_ending', 'built_form',
# 'walls_insulation_thickness_ending', 'potential_energy_efficiency',
# 'transaction_type_ending',
# 'floor_thermal_transmittance_ending',
# 'low_energy_lighting_ending', 'heat_demand_starting',
# 'photo_supply_ending', 'carbon_starting',
# 'walls_thermal_transmittance_ending',
# 'roof_insulation_thickness_ending',
# 'total_floor_area_ending', 'number_open_fireplaces_ending',
# 'windows_energy_eff_ending',
# 'floor_height_ending',
# 'extension_count_ending',
# 'has_air_source_heat_pump_ending',
# 'charging_system_ending', 'construction_age_band', 'glazed_type_ending',
# 'roof_thermal_transmittance_ending',
# 'floor_insulation_thickness_ending', 'has_mains_gas_ending',
# 'estimated_perimeter_starting', 'energy_consumption_potential',
# 'environment_impact_potential', 'heater_type_ending',
# 'multi_glaze_proportion_ending',
# 'lighting_energy_eff_ending', 'fixed_lighting_outlets_count']
'main-heating-controls'
]
generate_predictions:
input_dataclient_type: local

59
modules/ml-pipeline/src/pipeline/dvc.lock
View file

@ -48,7 +48,6 @@ stages:
- energy-consumption-current
- construction-age-band
- hotwater-description
- lodgement-datetime
- main-fuel
- hot-water-energy-eff
- co2-emiss-curr-per-floor-area
@ -58,28 +57,20 @@ stages:
- extension-count
- number-open-fireplaces
- number-heated-rooms
- lodgement-date
- windows-description
- local-authority
- photo-supply
- heat-loss-corridor
- posttown
- flat-top-storey
- unheated-corridor-length
- fixed-lighting-outlets-count
- inspection-date
- tenure
- county
- constituency-label
- multi-glaze-proportion
- solar-water-heating-flag
- energy-tariff
- floor-height
- constituency
- uprn-source
- transaction-type
- floor-energy-eff
- postcode
- lodgement-month
- lighting-cost-current
- glazed-area
@ -89,7 +80,7 @@ stages:
default.feature_processor.feature_processor_config.subsample_seed: 0
default.feature_processor.feature_processor_config.target: heating_kwh
default.feature_processor.feature_processor_type: dataframe
default.prepare_data.data_filepath:
default.prepare_data.data_filepath:
s3://retrofit-data-dev/energy_consumption/2024-07-25/energy_consumption_dataset.parquet
default.prepare_data.input_dataclient_type: aws-s3
default.prepare_data.output_dataclient_type: local
@ -99,8 +90,8 @@ stages:
outs:
- path: data/prepared_data/
hash: md5
md5: 8585e7f26fa0008dcc0074996a51a78d.dir
size: 18062621
md5: 240ceda2ba6ed38022d4ddf3271bccd0.dir
size: 10408173
nfiles: 2
build_model:
cmd: python 2_build_model.py
@ -111,8 +102,8 @@ stages:
size: 4820
- path: data/prepared_data
hash: md5
md5: 8585e7f26fa0008dcc0074996a51a78d.dir
size: 18062621
md5: 240ceda2ba6ed38022d4ddf3271bccd0.dir
size: 10408173
nfiles: 2
params:
configs/build_model.yaml:
@ -144,18 +135,18 @@ stages:
outs:
- path: data/fit_predictions/
hash: md5
md5: 0f536790b342ee84fe51f5bf66ca4e3c.dir
size: 1545512
md5: 449333eac4dd5a6538a39e08b448c838.dir
size: 1544880
nfiles: 1
- path: data/model/
hash: md5
md5: 0ce09cc5e2d12876d9315cb18f8b70a9.dir
size: 320950858
nfiles: 36
md5: 735d5925686a22e9ea80e1374f33204f.dir
size: 144468604
nfiles: 28
- path: metrics/fit_metrics.json
hash: md5
md5: 5c38cf3ad988c55fb9685d76c7da78b3
size: 216
md5: 01c3b9d6c0a08dff53f1532f78d36ecc
size: 219
generate_predictions:
cmd: python 3_generate_predictions.py
deps:
@ -165,13 +156,13 @@ stages:
size: 2464
- path: data/model
hash: md5
md5: 0ce09cc5e2d12876d9315cb18f8b70a9.dir
size: 320950858
nfiles: 36
md5: 735d5925686a22e9ea80e1374f33204f.dir
size: 144468604
nfiles: 28
- path: data/prepared_data
hash: md5
md5: 8585e7f26fa0008dcc0074996a51a78d.dir
size: 18062621
md5: 240ceda2ba6ed38022d4ddf3271bccd0.dir
size: 10408173
nfiles: 2
params:
configs/settings.yaml:
@ -183,8 +174,8 @@ stages:
outs:
- path: data/predictions/
hash: md5
md5: 9f32b5e943df8cd9336077b8daf2975c.dir
size: 163552
md5: c1b613aa06be5589de825ca877ff66c4.dir
size: 163496
nfiles: 1
generate_metrics:
cmd: python 4_generate_metrics.py
@ -195,13 +186,13 @@ stages:
size: 3484
- path: data/predictions
hash: md5
md5: 9f32b5e943df8cd9336077b8daf2975c.dir
size: 163552
md5: c1b613aa06be5589de825ca877ff66c4.dir
size: 163496
nfiles: 1
- path: data/prepared_data
hash: md5
md5: 8585e7f26fa0008dcc0074996a51a78d.dir
size: 18062621
md5: 240ceda2ba6ed38022d4ddf3271bccd0.dir
size: 10408173
nfiles: 2
params:
configs/settings.yaml:
@ -211,8 +202,8 @@ stages:
outs:
- path: metrics/metrics.json
hash: md5
md5: 752659c808d2bf0f176a0bf1ad7088a1
size: 223
md5: 08ea486b800e624059374ff5bef107d0
size: 218
generate_scenerio_metrics:
cmd: python 5_generate_scenarios.py
deps: