Experimental analysis of the performance of machine learning algorithms in the classification of navigation accident records

Abstract

This paper aims to evaluate the use of machine learning techniques in a database of marine accidents. We analyzed and evaluated the main causes and types of marine accidents in the Northern Fluminense region. For this, machine learning techniques were used. The study showed that the modeling can be done in a satisfactory manner using different configurations of classification algorithms, varying the activation functions and training parameters. The SMO (Sequential Minimal Optimization) algorithm showed the best performance result.

Keywords

• Machine Learning
• Brazilian Navy
• Data Mining
• K-Nearest Neighbor
• Multilayer Perceptron
• Bayesian Networks
• Sequential Minimal Optimization