The Decision Stump is a type of Decision Tree algorithm used in Supervised Learning. It is a one-level decision tree that is often used as a base classifier in many ensemble methods. Decision Stump: Introduction Domains Learning Methods Type Machine Learning Supervised Decision Tree Decision Stump is a type of decision tree…

& Code Conditional Decision Trees are a type of decision tree used in supervised and unsupervised learning. They are a tree-like model of decisions, where each node represents a feature, each link (branch) represents a decision rule, and each leaf represents an outcome. Conditional Decision Trees: Introduction Domains Learning Methods Type Machine Learning…

Examples & Code Classification and Regression Tree, also known as CART, is an umbrella term used to refer to various types of decision tree algorithms. It belongs to the category of Decision Trees and is primarily used in Supervised Learning methods. Classification and Regression Tree: Introduction Domains Learning Methods Type Machine Learning Supervised Decision…

Explanations, Examples & Code Chi-squared Automatic Interaction Detection, commonly known as CHAID, is a decision tree technique that falls under the category of supervised learning. It is based on adjusted significance testing and is utilized to identify the most significant predictors of a particular outcome. This algorithm is a popular…

Developed by Yandex, CatBoost (short for “Category” and “Boosting”) is a machine learning algorithm that uses gradient boosting on decision trees. It is specifically designed to work effectively with categorical data by transforming categories into numbers in a way that doesn’t impose arbitrary ordinality. …

Examples & Code Convolutional Neural Network (CNN), a class of deep neural networks, is widely used in pattern recognition and image processing tasks. CNNs can also be applied to any type of input that can be structured as a grid, such as audio spectrograms or time-series data. They are designed…

C5.0 is a decision tree algorithm used for supervised learning. It is an updated version of the earlier ID3 algorithm, and is widely used to generate decision trees. C5.0: Introduction Domains Learning Methods Type Machine Learning Supervised Decision Tree C5.0 is a decision tree algorithm that is widely used in supervised…

Examples & Code Convolutional Neural Network (CNN), a class of deep neural networks, is widely used in pattern recognition and image processing tasks. CNNs can also be applied to any type of input that can be structured as a grid, such as audio spectrograms or time-series data. They are designed…

The Bayesian Network (BN) is a type of Bayesian statistical model that represents a set of variables and their conditional dependencies via a directed acyclic graph. BN is a powerful tool in machine learning and artificial intelligence for modeling complex systems. In BN, variables are represented as nodes on a…