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  1. An algorithm (model, method) is called a classification algorithm if it uses the data and its classification to build a set of patterns: discriminant and /or characteristic rules or other pattern descriptions.

  2. Multilayer perceptrons combined multiple layers and use non-linear activation function, which makes them capable to classify data that is not linearly separable (more on this in later lectures)

  3. [Vertebrate Classification] Table 3.2 shows a sample data set for classifying vertebrates into mammals, reptiles, birds, fishes, and am-phibians. The attribute set includes characteristics of the vertebrate …

  4. The book will start off with an overview of the basic methods in data classification, and then discuss progressively more refined and complex methods for data classification.

  5. ANN—Artificial Neural Network (Classification by Backpropagation) An artificial neural network is an interconnected group of nodes, akin to the vast network of neurons in a brain.

  6. This publication defines basic terminology and explains fundamental concepts in data classification so there is a common language for all to use. It can also help organizations improve the quality and …

  7. Data Mining Classification: Basic Concepts, Decision Trees, and Model Evaluation Lecture Notes for Chapter 4