Lessmann, S., et al. (2015) Benchmarking State-of-the-Art Classification Algorithms for Credit Scoring. Journal of the Operational Research Society, 66, 743-755.

created and refined classification models on the Sonar dataset using Random Forest and Logistic Regression, reaching up to 89% accuracy through 5-fold cross-validation and hyperparameter tuning. - ...

The study quantified characteristics of the research data set with 26 indicators, including simple indicators, statistical indicators and information theory indicators. Eight machine learning ...

Accurate classification is essential for the safety of naval operations and is a difficult problem in marine mine removal. In this research, this study compares and contrasts six popular machine ...

Figure 2 shows the accuracy measurements for the exhaustive grid exploration of Λ on the random classification dataset Figure 1D. The corresponding pseudo-code is given in Algorithm 1. Before applying ...

random-forest Random Forest Algorithm Python Implementation using Sonar Dataset. Random forest algorithm is a supervised classification algorithm. As the name suggest, this algorithm creates the ...

An improved method for transient sonar signal classification is presented. In the ocean, noise exists nearly everywhere and the accuracy of classifying sonar signals is decreased to some extent. To ...