predicting_sim: Simulation of Scheduling Jobs Based On Predictions.

In carlonlv/DataCenterSim: Simulations for Data Centers

Description

Sequantially training and testing by scheduling a job.

Usage

predicting_sim(
  object,
  x,
  xreg,
  start_point = 1,
  wait_time = 0,
  cores,
  write_type,
  plot_type,
  ...
)

Arguments

object	A uni-length sim object that represents a specific parameter setting.
x	A matrix of size n by m representing the target dataset for scheduling and evaluations.
xreg	A matrix of length n by m representing the dataset that target dataset depends on for scheduling and evaluations.
start_point	A numeric number that represents the starting point of the simulation. Default value is 1.
wait_time	A numeric number that represents the time between training and testing. Default value is 0.
cores	The number of threads for parallel programming for multiple traces, not supported for windows users.
write_type	A character that represents how to write the result of simulation, can be one of "charwise", "tracewise", "paramwise" or "none".
plot_type	A character that represents how to plot the result of simulation can be one of "charwise", "tracewise", "paramwise" or "none".
...	Characters that represent the name of parent directories that will be passed to write_location_check.

Value

An S4 sim result object.

carlonlv/DataCenterSim documentation built on Jan. 9, 2022, 3:26 p.m.