40.220 The Analytics Edge (SUTD) 2024 In this competition, we were tasked to predict the choice among bundles of safety features in cars. This data was analyzed in Weeks 4 and 5 of the classes. We've used a combination of Random Forest, Multinomial and Support Vector Machine models.
| Info | .R | .csv |
|---|---|---|
| Train | - | train2024.csv |
| Test | - | test2024.csv |
| Dependencies Installation | Dependencies.R | - |
| Model 1: Random Forest (RF) + Multinomial (Mlogit) | Initial_MultinomForest.R | initial_multinomforest.csv |
| Support Vector Machine (SVM) Linear | SVM_Linear.csv | svm_linear.csv |
| Support Vector Machine (SVM) Radial | SVM_Radial.csv | svm_radial.csv |
| Model 2: SVM Linear + RF + MLogit | Model2.R | model2.csv |
| Model 3: SVM Linear + Radial | Model3.R | model3.csv |
| Adjusted RF + MLogit | AdjustedMultinomForest.R | adjustedmultinomforest.csv |
| Model 4: 0.5(SVM Linear + Radial) + 0.5(Adjusted RF + MLogit) | Model4.R | model4.csv |
Please ensure you have at least R 4.3.3 version installed and RStudio. Both latest R and RStudio can be installed here: https://posit.co/download/rstudio-desktop/
- Clone this repository through git clone onto your computer via your command prompt.
- Run Dependencies.R first to install all the necessary packages.
- For each R code, please remember to set your working directory to the this repository through
setwdFor example,
setwd("C:\\Users\\File\\Path\\To\\Code") #Note the double \\- Run the code in order from from top to bottom based on the .R column in the table shown above.
- The .csv results are already in the file. If you would like to verify the best solution, run Model4.R only
Team 11 (2024)
- Paige Trinity Tan (1006972)
- Li Xing (1007031)
- Tan Yan Zu, Joe (1006864)
- Destor Rose Evangeline Anne Dagman (1006988)