calc_features15_consumption |
Calculates features from 15-min smart meter data |
calc_features30_consumption |
Calculates features from 30-min smart meter data |
calc_features60_consumption |
Calculates features from 15-min smart meter data |
calc_featuresco_consumption |
Calculates consumption features from weekly consumption only |
calc_featuresda_consumption |
Calculates consumption features from daily smart meter data |
calc_featureshtnt_consumption2 |
Calculates consumption features from daily (HT / NT) smart meter data |
calc_featuresnt_consumption |
Calculates consumption features from daily (HT / NT) smart meter data |
calc_features_daily_multipleTS |
Calculates feature from multiple time series data vectors |
calc_features_weather |
Calculates features from one environmental time-series variable and smart meter data |
encode_p_val_stars |
Encodes p-values with a star rating according to the Significance code: |
features_all_subsets |
Creates a set of all combinations of features |
getDay_ISO8601_week |
Retrieves the date of the monday in a ISO8601 week-string |
getDay_US_week |
Retrieves the date of the monday in a US week-string (as implemented by R as.Date) |
interpolate_missingReadings |
Interpolate missing readings |
naInf_omit |
Removes the rows with NA or Inf values |
occupancy_cluster |
Determines two clusters of high and low consumption times (e.g., non-ocupancy during holidays) |
prepareFeatureSet |
Compiles a list of features from energy consumption data |
remove_empty_features |
Removes variables with no necessary information from a data.frame |
replaceNAsFeatures |
Replaces NA values with a given ones |
smote |
Synthetic minority oversampling (SMOTE) |