towt_baseline: Time Of the Week and Temperature baseline model function.
In LBNL-ETA/RMV2.0: M&V2.0 Using R and Shiny

towt_baseline This function builds a baseline model using gradient boosting machine algorithm.

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towt_baseline(train_path = NULL, pred_path = NULL, train_Data = NULL,
  pred_Data = NULL, timescaleDays = 14, verbosity = 1,
  intervalMinutes = 15, fahrenheit = T)

`train_path`	The path of the file from which the training data are to be read from.
`pred_path`	The path of the file from which the prediction data are to be read from.
`train_Data`	A dataframe, of the training period, where the columns correspond to the time steps (time), the energy load (eload) and to the Temperature (Temp).
`pred_Data`	A dataframe, of the prediction period, where the columns correspond to the time steps (time), the energy load (eload) and to the Temperature (Temp).
`timescaleDays`	Numeric correspond to the timescale for weighting function.
`verbosity`	Numeric that determine what progress and error reports to print .
`intervalMinutes`	Numeric of length of a Time Of Week interval as input variables.
`fahrenheit`	Boolean that determine if the temperatures are in Fahrenheit.

a towt_baseline object, which alist with the following components:

towt_model: an object that has been created by the function makeBaseline, and which correspond to the towt model.
train: a data frame that correspond to the training data after the cleaning and filtering function were applied.
fitting: the fitted values.
goodness_of_fit: a data frame that contains the goodness of fitting metrics.
pred: a data frame that correspond to the prediction data after the cleaning and filtering function were applied.
prediction: the predicted values.