This analysis evaluates public interest in espresso coffee using support vector machine and naïve bayes algorithms, showing predictive accuracy differences.
Key Points
Naïve Bayes outperforms Support Vector Machine in accuracy and other metrics.
Naïve Bayes achieved 94.00% accuracy compared to 90.00% for Support Vector Machine.
Classification algorithms were used to analyze public interest in buying espresso coffee.
This study highlights the importance of choosing the right algorithm for predictive modeling.