Learning Goal: I’m working on a machine learning project and need an explanation and answer to help me learn.https://www.kaggle.com/c/house-prices-advanced-regression-techniques/ overviewYou may participate in the Kaggle competition if you like, but you are NOT required to participate for this midterm project. The midterm project is a regression forecasting exercise. You are expected to build forecasting models to predict the sale price (the endogenous variable) using: OLS
and 3 machine learning methods
The three machine learning methods may include KNN, Ridge, LASSO and Elastic Net, but you can also use other methods like random forests or neural networks if you choose. You can do the analysis in Python, Stata, R or any other software of your choice. The les included in the dataset are the following: data description.csv
You only need “data description.txt” and “train.csv” if you are not participating in the Kaggle competition. “test.csv” includes test data without the sale prices for the competition. You will not be able to calculate the RMSE using the data in “test.csv”. You will need to create your own test set (from train.csv”) to calculate the RMSE. You are also required to write a report. In this report, make sure to include the following information: Describe the data
Describe data cleaning
Describe how the data was split into the training and the test set; what
% of observations are in each? How did you allocate them randomly? Describe the 4 methods used
Discuss the hyperparameters for each methods; explain what they do
Explain how you have tuned the hyperparameters
Report the RMSE for each method at the optimal hyperparameter
values Graph the RMSE at a range of hyperparameters that includes the
optimal value; make sure to label your graph and include the OLS RMSE as reference Comment on the performance of the 4 methods used; are the ML
techniques improving the forecast relative to OLS? Why? Explain.Make sure to submit your report and your code (for replication). The code should include comments describing the work that you are doing. The project can be completed on your own or in groups of two students. Include the name and student numbers of both students on the report and in the code. The code must be your own and should not be a copy-paste of code from other groups or anywhere else.
Requirements: This is a midterm project | .doc file
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