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_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
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
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)
