ParallelInit: As a data ParallelIniting function, sets some global...

In ParallelDSM: Parallel Digital Soil Mapping using Machine Learning

As a data ParallelIniting function, sets some global variables that are not visible to the user

Description

As a data ParallelIniting function, sets some global variables that are not visible to the user

Usage

ParallelInit(
  Fpath = "",
  fn = "",
  dsmformula = "",
  nblock = 6,
  ncore = 2,
  Fc = 1
)

Arguments

Fpath	: The file path to the CSV file
fn	: Name of the folder in which the soil data is stored
dsmformula	: Symbolic description of a soil fitting model
nblock	: the number of blocks for data cutting
ncore	: Computes the CPU's kernel in parallel(fill in according to the computer configuration)
Fc	: the encoding of file

References

Breiman, L. (2001). Random forests. Mach. Learn. 45, 5???32. Meinshausen, N. (2006) "Quantile Regression Forests", Journal of Machine Learning Research 7, 983-999 http://jmlr.csail.mit.edu/papers/v7/

Examples

############################################################################
## Example code                                                           ##
## Select your own reading method, as shown below                         ##
############################################################################
mydatas <- system.file("extdata", "all.input.csv", package = "ParallelDSM")
sampledatas <- system.file("extdata", "covariate", package = "ParallelDSM")
ParallelInit(mydatas,sampledatas,"socd030 ~ twi + dem + pa")

############################################################################
## If you want to use test cases, load the relevant data sets             ##
############################################################################
# Select the data set that comes with this package
# data("df.input", package = "ParallelDSM")
# data("df.dem", package = "ParallelDSM")

############################################################################
##  Use the data file references that come with this package              ##
############################################################################
# sampledatas <- system.file("extdata", "covariate", package = "ParallelDSM")

############################################################################
## Select your own data file references, as shown below                   ##
############################################################################
# sampledatas <- "C:/mySampleDatas/"

############################################################################
## Use ParallelInit functions to process the data that is loaded in       ##
############################################################################
# ParallelInit(myinput,sampledata,"socd030 ~ twi + procur + dem")

############################################################################
## This function is the main function that performs parallel computations ##
## The outpath field refers to the filename of the data output            ##
## The mymodels field has three modes to choose from: QRF,RF and MLR      ##
## 'QRF' stands for Quantile Regression Forest Model Prediction Method    ##
## 'RF' stands for Random Forest Model Prediction Method                  ##
## 'MLR' stands for Multiple Linear Regression Prediction Model           ##
## 'from' and 'to' are reserved fields that can be left unused by the user##
############################################################################
# ParallelComputing(outpath = "myoutputs", mymodels = "MLR")

ParallelDSM documentation built on Nov. 16, 2022, 9:05 a.m.