ARTIFICIAL INTELLIGENCE TECHNIQUES FOR CLASSIFICATION: CLUSTER ANALYSIS AND KNN CLASSIFIERS. Examples with MATLAB

Today, the amount of data generated by both humans and machines far exceeds the ability of humans to absorb, interpret, and make complex decisions based on that data. Artificial Intelligence is the foundation of all machine learning and the future of all complex decision-making processes. Artificial Intelligence combines mathematical algorithms and techniques from Machine Learning, Deep Learning, and Big Data to extract the knowledge contained in the data and present it in an understandable and automatic way. This book develops AI classification techniques. Cluster Analysis, Hierarchical Cluster, Non Hierarchical Cluster, K-Means, Gaussian Mixture Models, Hidden Markov Chains, Nearest Neighbors, kNN Classifiers, Clusters Visualization, Clusters Evaluation, Clustering with Neural Network, Clustering with Self Organizing Maps, Competitive Neural Networks, Competitive Layers, And Autoencoders are included.