Hakutulokset: Sarja unsupervised and semi-supervised learning
yhteensä 16 hakutulosta
Linking and Mining Heterogeneous and Multi-view Data
This book highlights research in linking and mining data from across varied data sources. The authors focus on recent advances in this burgeoning field of multi-source data fusion, …
Unsupervised Feature Extraction Applied to Bioinformatics
This updated book proposes applications of tensor decomposition to unsupervised feature extraction and feature selection. The author posits that although supervised methods …
Feature and Dimensionality Reduction for Clustering with Deep Learning
This book presents an overview of recent methods of feature selection and dimensionality reduction that are based on Deep Neural Networks (DNNs) for a clustering perspective, with …
Sampling Techniques for Supervised or Unsupervised Tasks
This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It …
Deep Biometrics
This book highlights new advances in biometrics using deep learning toward deeper and wider background, deeming it “Deep Biometrics”. The book aims to highlight recent developments …
Supervised and Unsupervised Learning for Data Science
This book covers the state of the art in learning algorithms with an inclusion of semi-supervised methods to provide a broad scope of clustering and classification solutions for …
Machine Learning and Data Analytics for Solving Business Problems
This book presents advances in business computing and data analytics by discussing recent and innovative machine learning methods that have been designed to support decision-making …
Mixture Models and Applications
This book focuses on recent advances, approaches, theories and applications related to mixture models. In particular, it presents recent unsupervised and semi-supervised frameworks …
Unsupervised Feature Extraction Applied to Bioinformatics
This book proposes applications of tensor decomposition to unsupervised feature extraction and feature selection. The author posits that although supervised methods including deep …
Clustering Methods for Big Data Analytics
This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters …
Natural Computing for Unsupervised Learning
This book highlights recent research advances in unsupervised learning using natural computing techniques such as artificial neural networks, evolutionary algorithms, swarm …
Hidden Markov Models and Applications
This book focuses on recent advances, approaches, theories, and applications related Hidden Markov Models (HMMs). In particular, the book presents recent inference frameworks and …