supervised learning

CatBoost Algorithm

What is CatBoost Algorithm? CatBoost (Categorical Boosting) is a gradient boosting algorithm developed by Yandex. It is specifically designed to handle categorical features efficiently and automatically, without requiring extensive preprocessing…

Gradient Boosting Algorithm

Gradient Boosting is one of those rare ideas in machine learning that’s both simple at its core and remarkably powerful in practice. From credit scoring and click-through prediction to anomaly…

Extreme Learning Machine (ELM): Fast Learning Algorithm for Single-Layer Feedforward Networks

What is Extreme Learning Machine (ELM) Algorithm? A quick and effective machine learning approach for training Single Hidden Layer Feedforward Neural Networks (SLFNs) is called Extreme Learning Machine (ELM). ELM…

K-Nearest Neighbors (KNN) Algorithm: Classification, Working & Real-World Applications

What is k-Nearest Neighbors (k-NN)? A supervised learning approach for classification and regression problems is called k-Nearest Neighbors (k-NN). Since it is instance-based and non-parametric, it does not explicitly learn…

Naive Bayes Algorithm: Working Principle, Types & Applications in Machine Learning

What is Naïve Bayes Algorithm? Naïve Bayes is a probabilistic classification algorithm that relies on Bayes’ Theorem. It assumes that all features in the dataset are independent of one another.…

Multilayer Perceptron (MLP): Architecture, Working & Applications in Neural Networks

What is Multilayer Perceptron (MLP) ? An input layer, one or more hidden layers, and an output layer are among the several layers of neurons that make up a multilayer…

Artificial Neural Networks (ANN): Architecture, Learning Process & Applications in AI

ANN Algorithm A computational model called an artificial neural network (ANN) is modeled after the composition and operations of the human brain. It is a crucial part of deep learning…