Sailboat Price Prediction

Motivation

The global sailboat market has grown from $6.35 billion to $6.43 billion in the past year and is projected to reach $7.46 billion by 2029 [1], highlighting the worldwide importance of sailboats. Accurate sailboat price prediction would benefit consumers by preventing overpayment, enable sellers to set fair prices, support businesses in forecasting earnings, and guide investors in making informed decisions.

Sailboat Market Trend [The accuracyss Research Company, "Sailboat Global Market Report 2025," MarketResearch.com, Jul. 2025.]

Goal

The goal of this work is to develop efficient sailboat price prediction methodologies by leveraging machine learning (linear, boosting) and deep learning techniques.

Results

We trained and evaluated multiple models, including linear regression, decision tree, random forest, support vector regression, K-nearest regressor, AdaBoost, CatBoost, XGBoost, multilayer perceptron, and 1D Convolutional Neural Networks. Experimental results demonstrate strong performance across models, with the 1D CNN achieving the highest R² score of 0.887, confirming the effectiveness of deep learning for accurate sailboat price prediction.

Publications

Listed below are our publications based on this research:

Anish Roy, et. al., "Efficient Sailboat Price Prediction Using Linear, Boosting and Deep Learning Models", accepted, IEEE International Conference on Computing (ICOCO), 6-8 Oct 2025, Malaysia.