On combining artificial neural nets
AJC SHARKEY - Connection science, 1996 - Taylor & Francis
This paper reviews research on combining artificial neural nets, and provides an overview
of, and an introduction to, the papers contained in this special issue, and its companion …
of, and an introduction to, the papers contained in this special issue, and its companion …
[图书][B] Model-based clustering and classification for data science: with applications in R
Cluster analysis finds groups in data automatically. Most methods have been heuristic and
leave open such central questions as: how many clusters are there? Which method should I …
leave open such central questions as: how many clusters are there? Which method should I …
Ensemble-based classifiers
L Rokach - Artificial intelligence review, 2010 - Springer
The idea of ensemble methodology is to build a predictive model by integrating multiple
models. It is well-known that ensemble methods can be used for improving prediction …
models. It is well-known that ensemble methods can be used for improving prediction …
Twenty years of mixture of experts
In this paper, we provide a comprehensive survey of the mixture of experts (ME). We discuss
the fundamental models for regression and classification and also their training with the …
the fundamental models for regression and classification and also their training with the …
[图书][B] Data mining with decision trees: theory and applications
Decision trees have become one of the most powerful and popular approaches in
knowledge discovery and data mining; it is the science of exploring large and complex …
knowledge discovery and data mining; it is the science of exploring large and complex …
[图书][B] Finite mixture and Markov switching models
S Frühwirth-Schnatter - 2006 - Springer
Modelling based on finite mixture distributions is a rapidly developing area with the range of
applications exploding. Finite mixture models are nowadays applied in such diverse areas …
applications exploding. Finite mixture models are nowadays applied in such diverse areas …
Concomitant variables in finite mixture models
M Wedel - Statistica Neerlandica, 2002 - Wiley Online Library
The standard mixture model, the concomitant variable mixture model, the mixture regression
model and the concomitant variable mixture regression model all enable simultaneous …
model and the concomitant variable mixture regression model all enable simultaneous …
[图书][B] Pattern classification using ensemble methods
L Rokach - 2010 - books.google.com
1. Introduction to pattern classification. 1.1. Pattern classification. 1.2. Induction algorithms.
1.3. Rule induction. 1.4. Decision trees. 1.5. Bayesian methods. 1.6. Other induction …
1.3. Rule induction. 1.4. Decision trees. 1.5. Bayesian methods. 1.6. Other induction …
Demystifying softmax gating function in Gaussian mixture of experts
Understanding the parameter estimation of softmax gating Gaussian mixture of experts has
remained a long-standing open problem in the literature. It is mainly due to three …
remained a long-standing open problem in the literature. It is mainly due to three …
[图书][B] Ensemble learning: pattern classification using ensemble methods
L Rokach - 2019 - World Scientific
Artificial intelligence (AI) is a scientific discipline that aims to create intelligent machines.
Machine learning is a popular and practical AI subfield that aims to automatically improve …
Machine learning is a popular and practical AI subfield that aims to automatically improve …