Figure 4.
The image displays a vertical bar graph comparing the performance of four algorithms, Random Forest, Gradient Boosting, Decision Tree, and Logistic Regression. The y axis indicates the performance scores ranging from zero point seventy five to one, while the x axis categorises the data into three segments, Financial Ratios, Raw Data of Financial Ratios, and Raw Data. Each algorithm’s scores are represented by differently coloured bars, blue for Random Forest, orange for Gradient Boosting, grey for Decision Tree, and yellow for Logistic Regression. The graph highlights specific performance values for each algorithm across the three categories, showing variations in scores. The tallest bars in both the Raw Data categories belong to Random Forest and Gradient Boosting, with unique scores presented next to the corresponding bars, such as zero point ninety nine for both algorithms in the Raw Data category.AUC results: random forest outperforms the other classifiers after the application of random undersampling