Machine learning model used to predict the auction sale price of heavy equipment based on previous records
Name: Heavy Equipment Price Predictor
Author: Sharome Burton
Date: 07/17/2021
Description: Machine learning model used to predict the auction sale price of heavy equipment
How well can we predict the future sale price of a piece of heavy equipment(eg. a bulldozer), given its characteristics and previous examples of how much similar machines have been sold for?
The data for this project can be downloaded from the Kaggle Bluebook for Bulldozers competition: https://www.kaggle.com/c/bluebook-for-bulldozers/data
There are 3 main datasets:
Train.csv is the training set, which contains data through the end of 2011.Valid.csv is the validation set, which contains data from January 1, 2012 - April 30, 2012 You make predictions on this set throughout the majority of the competition. Your score on this set is used to create the public leaderboard.Test.csv is the test set, which won’t be released until the last week of the competition. It contains data from May 1, 2012 - November 2012. Your score on the test set determines your final rank for the competition.The evaluation metric for this competition is the RMSLE (root mean squared log error) between the actual and predicted auction prices.
For more on the evaluation of this project check: https://www.kaggle.com/c/bluebook-for-bulldozers/overview/evaluation
Kaggle provides a data dictionary detailing all of the features of the dataset. You can view this data dictionary on Google Sheets: https://docs.google.com/spreadsheets/d/18ly-bLR8sbDJLITkWG7ozKm8l3RyieQ2Fpgix-beSYI/edit?usp=sharing