Learning Vector Quantization
Ever wondered how machines can learn to classify data? Enter Learning Vector Quantization (LVQ), a powerful algorithm for supervised classification tasks. Let's dive into the details! Learn Vector Quantization (or LVQ) is a type of Artificial Neural Network that is also influenced by the biological model that represents neural networks. It is based on a prototype algorithm for supervised learning and classification. It has developed its network using an algorithm of competitive learning similar to the Self Organizing Map. It is also able to deal with the problem of multiclass classification. LVQ aims to learn a set of reference vectors (prototypes) representing different classes in a labelled dataset. These prototypes will help classify new, unseen examples effectively . 🔢 Step-by-Step Overview: 1️ ⃣ Initialization: Randomly select reference vectors, based on the number of classes in the dataset. 2️ ⃣ Distance Calculation: Measure ...