Weight: Selection of Superior Models Using MSC Algorithm

In EEML: Ensemble Explainable Machine Learning Models

Selection of Superior Models Using MSC Algorithm

Description

Selection of Superior Models Using MSC Algorithm

Usage

Weight(ModelSel, Optim = "PSO")

Arguments

ModelSel	Dataframe of predicted values of selected models with first column as actual values
Optim	Optimisation technique

Value

• WeightEn: Ensemble weight of the candidate models

References

• Paul, R.K., Das, T. and Yeasin, M., 2023. Ensemble of time series and machine learning model for forecasting volatility in agricultural prices. National Academy Science Letters, 46(3), pp.185-188.

• Yeasin, M. and Paul, R.K., 2024. OptiSembleForecasting: optimization-based ensemble forecasting using MCS algorithm and PCA-based error index. The Journal of Supercomputing, 80(2), pp.1568-1597.

Examples

library("EEML")
Actual<- as.ts(rnorm(200,100,50))
Model1<- as.ts(rnorm(200,100,50))
Model2<- as.ts(rnorm(200,100,50))
Model3<- as.ts(rnorm(200,100,50))
DF <- cbind(Actual, Model1,Model2,Model3)
SelModel<-Weight(ModelSel=DF,Optim="PSO")

EEML documentation built on Sept. 11, 2024, 6:54 p.m.