by Gabriel Tam | May 16, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub
Minimum Description Length, often shortened to MDL, is a principle used in machine learning and data analysis to help identify models that best explain a dataset while avoiding unnecessary complexity. The main idea behind MDL is that the best model is one that...
by Gabriel Tam | May 9, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub
Neural networks are a machine learning technique inspired by the way the human brain processes information. They are designed to recognize patterns, learn from data, and make predictions by analyzing relationships between inputs and outputs. Neural networks are...
by Gabriel Tam | May 2, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub
Decision trees are a supervised machine learning technique used for both classification and regression tasks. They work by breaking down a problem into a series of simple decisions, creating a tree like structure of rules that lead to a final outcome. Each step in the...
by Gabriel Tam | Apr 25, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub
XGBoost, short for Extreme Gradient Boosting, is a powerful machine learning algorithm used mainly for supervised learning tasks such as classification and regression. It is based on the idea of combining multiple simple models, typically decision trees, to create a...
by Gabriel Tam | Apr 18, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub
Ranking is a machine learning technique used to order items based on their relevance, importance, or likelihood of a particular outcome. Rather than simply predicting a value or assigning a category, ranking focuses on prioritizing results so that the most useful or...
by Gabriel Tam | Apr 11, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub
Row importance is a machine learning technique used to identify which individual records in a dataset are the most significant or influential. While many techniques focus on the importance of variables, row importance shifts the focus to the data points themselves. It...
