mirror of
https://github.com/Hestia-Homes/ML.git
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add estimate_annual_kwh feature, remove env features
This commit is contained in:
Michael Duong
parent
ec7149e56e
commit
a10be25fd2
3 changed files with 45 additions and 144 deletions
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@ -160,7 +160,9 @@ def add_features_from_code(df):
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return df
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def add_estimate_annual_kwh(df):
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df['estimate_annual_kwh'] = df['energy-consumption-current'] * df['total-floor-area']
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return df
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# def keep_ending_columns(df):
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# ending_column_index = [ col_name.endswith("_ENDING") for col_name in list(df.columns)]
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@ -172,7 +174,8 @@ def add_features_from_code(df):
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business_logic = {
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"add_features_from_code": add_features_from_code,
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"remove_hotwaterkwh_bottom_percentile": remove_hotwaterkwh_bottom_percentile
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"remove_hotwaterkwh_bottom_percentile": remove_hotwaterkwh_bottom_percentile,
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"add_estimate_annual_kwh": add_estimate_annual_kwh
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# "keep_non_zero_rdsap": keep_non_zero_rdsap,
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# "keep_flats": keep_flats,
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# "remove_minimum_habitable_room_size": remove_minimum_habitable_room_size,
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@ -30,75 +30,9 @@ default:
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subsample_seed: 0
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target: hot_water_kwh
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identifier_columns: ["uprn"]
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drop_columns: ["heating_kwh"]
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retain_features: [
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'uprn',
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'heating-cost-current',
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'co2-emissions-current',
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'hot-water-cost-current',
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'total-floor-area',
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'secondheat-description',
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'environment-impact-current',
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'floor-description',
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'mainheat-energy-eff',
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'current-energy-efficiency',
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'mainheat-env-eff',
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'walls-energy-eff',
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'roof-energy-eff',
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'property-type',
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'mainheat-description',
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'hot-water-env-eff',
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'mechanical-ventilation',
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'floor-level',
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'built-form',
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'walls-description',
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'mainheatcont-description',
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'roof-description',
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'energy-consumption-current',
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'construction-age-band',
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'hotwater-description',
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# 'lodgement-datetime',
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'main-fuel',
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'hot-water-energy-eff',
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'co2-emiss-curr-per-floor-area',
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'windows-energy-eff',
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'current-energy-rating',
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'lodgement-year',
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'extension-count',
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'number-open-fireplaces',
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'number-heated-rooms',
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# 'lodgement-date',
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# 'number-habitable-rooms',
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'windows-description',
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# 'local-authority',
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'photo-supply',
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'heat-loss-corridor',
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# 'posttown',
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# 'address',
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'flat-top-storey',
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'unheated-corridor-length',
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'fixed-lighting-outlets-count',
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# 'inspection-date',
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'tenure',
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# 'county',
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# 'constituency-label',
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'multi-glaze-proportion',
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'solar-water-heating-flag',
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# 'address2',
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'energy-tariff',
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'floor-height',
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'constituency',
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# 'uprn-source',
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'transaction-type',
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'floor-energy-eff',
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# 'postcode',
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'lodgement-month',
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'lighting-cost-current',
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'glazed-area',
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# 'address1',
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'floor-env-eff',
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'main-heating-controls'
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]
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drop_columns: ["heating_kwh", 'lodgement-datetime', 'lodgement-date', 'number-habitable-rooms', 'local-authority', 'posttown', 'address', 'inspection-date',
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"county", "constituency-label", 'address2', 'uprn-source', 'postcode', 'address1', 'mainheat-env-eff', 'environment-impact-current', 'hot-water-env-eff', 'floor-env-eff']
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retain_features: null
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generate_predictions:
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input_dataclient_type: local
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@ -22,60 +22,24 @@ stages:
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configs/settings.yaml:
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default.feature_processor.feature_processor_config.drop_columns:
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- heating_kwh
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default.feature_processor.feature_processor_config.retain_features:
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- uprn
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- heating-cost-current
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- co2-emissions-current
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- hot-water-cost-current
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- total-floor-area
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- secondheat-description
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- environment-impact-current
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- floor-description
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- mainheat-energy-eff
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- current-energy-efficiency
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- lodgement-datetime
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- lodgement-date
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- number-habitable-rooms
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- local-authority
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- posttown
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- address
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- inspection-date
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- county
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- constituency-label
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- address2
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- uprn-source
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- postcode
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- address1
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- mainheat-env-eff
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- walls-energy-eff
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- roof-energy-eff
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- property-type
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- mainheat-description
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- environment-impact-current
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- hot-water-env-eff
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- mechanical-ventilation
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- floor-level
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- built-form
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- walls-description
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- mainheatcont-description
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- roof-description
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- energy-consumption-current
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- construction-age-band
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- hotwater-description
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- main-fuel
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- hot-water-energy-eff
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- co2-emiss-curr-per-floor-area
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- windows-energy-eff
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- current-energy-rating
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- lodgement-year
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- extension-count
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- number-open-fireplaces
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- number-heated-rooms
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- windows-description
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- photo-supply
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- heat-loss-corridor
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- flat-top-storey
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- unheated-corridor-length
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- fixed-lighting-outlets-count
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- tenure
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- multi-glaze-proportion
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- solar-water-heating-flag
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- energy-tariff
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- floor-height
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- constituency
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- transaction-type
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- floor-energy-eff
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- lodgement-month
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- lighting-cost-current
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- glazed-area
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- floor-env-eff
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- main-heating-controls
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default.feature_processor.feature_processor_config.retain_features:
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default.feature_processor.feature_processor_config.subsample_amount:
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default.feature_processor.feature_processor_config.subsample_seed: 0
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default.feature_processor.feature_processor_config.target: hot_water_kwh
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@ -90,8 +54,8 @@ 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: 295ac4fd05a1a3373401a7318b0b5186.dir
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size: 13131853
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md5: 0364b2ef5dd7674f97473fdecf3f3a02.dir
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size: 35173792
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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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@ -102,8 +66,8 @@ stages:
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size: 4820
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- path: data/prepared_data
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hash: md5
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md5: 295ac4fd05a1a3373401a7318b0b5186.dir
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size: 13131853
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md5: 0364b2ef5dd7674f97473fdecf3f3a02.dir
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size: 35173792
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nfiles: 2
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params:
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configs/build_model.yaml:
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@ -135,17 +99,17 @@ stages:
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outs:
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- path: data/fit_predictions/
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hash: md5
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md5: 3e48cec68f702bc822eed8fcb2c5c603.dir
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size: 1787931
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md5: 56598af2325ec699349cdb166b1e807b.dir
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size: 1789771
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nfiles: 1
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- path: data/model/
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hash: md5
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md5: 37f7480141e920c68faacd39478a1a68.dir
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size: 451364406
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nfiles: 35
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md5: ce995d18c2f40aefe1f5757d621bb4d4.dir
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size: 592064916
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nfiles: 36
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- path: metrics/fit_metrics.json
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hash: md5
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md5: e7a2a5efea57b1ddd1431b713d78bb11
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md5: 4c169dc1d437e5fea43e47616f46dafc
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size: 219
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generate_predictions:
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cmd: python 3_generate_predictions.py
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@ -156,13 +120,13 @@ stages:
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size: 2464
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- path: data/model
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hash: md5
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md5: 37f7480141e920c68faacd39478a1a68.dir
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size: 451364406
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nfiles: 35
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md5: ce995d18c2f40aefe1f5757d621bb4d4.dir
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size: 592064916
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nfiles: 36
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- path: data/prepared_data
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hash: md5
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md5: 295ac4fd05a1a3373401a7318b0b5186.dir
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size: 13131853
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md5: 0364b2ef5dd7674f97473fdecf3f3a02.dir
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size: 35173792
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nfiles: 2
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params:
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configs/settings.yaml:
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@ -174,8 +138,8 @@ stages:
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outs:
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- path: data/predictions/
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hash: md5
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md5: 9267a66c6fae4da5a589faab76fac14c.dir
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size: 192482
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md5: 590da9bdeb1e1b442e52bce52f1da0dc.dir
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size: 192586
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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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@ -186,13 +150,13 @@ stages:
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size: 3484
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- path: data/predictions
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hash: md5
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md5: 9267a66c6fae4da5a589faab76fac14c.dir
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size: 192482
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md5: 590da9bdeb1e1b442e52bce52f1da0dc.dir
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size: 192586
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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: 295ac4fd05a1a3373401a7318b0b5186.dir
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size: 13131853
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md5: 0364b2ef5dd7674f97473fdecf3f3a02.dir
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size: 35173792
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nfiles: 2
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params:
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configs/settings.yaml:
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@ -202,7 +166,7 @@ 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: 3a08c29f028f5e3cb50fb8cd3608e2f4
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md5: b80014eacb59a824aff78667352e7c95
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size: 221
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generate_scenerio_metrics:
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cmd: python 5_generate_scenarios.py
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