The project will involve investigating the following dataset: The Ames Iowa housing dataset.
The main question of interest in this dataset is How do home features add up to its price tag? This analysis involves forming a predictive model for the response variable, SalePrice, as a function of the 79 predictor variables. The 79 predictor variables are described in the file data description.txt.
R Markdown
- explore data analysis
- collinear problems
- feature selection
- dimension reduction
- regression models (Ridge/Lasso/PCR/PLS)
- data_description.txt: source variables description
- train.csv: the dataset of all training data for SalePrice
- test_new.csv: the dataset of all testing data for SalePrice
- House Price Prediction.Rmd: the code in R MarkDown
- House Price Prediction.pdf: the final report
- Final Presentation.pptx: the presentation slides
- README.md