A Naive Bayes Classifier is a supervised machine-learning algorithm that uses the Bayes’ Theorem, which assumes that features are statistically independent. The theorem relies on
Previously in this series, we have looked at decision trees and random forests, two types of supervised learning algorithms. Supervised algorithms are trained with data that
Random Forests are supervised ensemble-learning models used for classification and regression. Ensemble learning models aggregate multiple machine learning models, allowing for overall better performance. The
Recently, we published a research paper showing how it is possible to detect fraudulent credit card transactions with a high level of accuracy and a
A Decision Tree is a supervised predictive model that can learn to predict discrete or continuous outputs by answering a set of simple questions based
Online, or real-time, transactional fraud detection systems have recently created quite the buzz in the info security industry. They are an appealing concept: Because we
