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 …

[图书][B] Model-based clustering and classification for data science: with applications in R

C Bouveyron, G Celeux, TB Murphy, AE Raftery - 2019 - books.google.com
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 …

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 …

Twenty years of mixture of experts

SE Yuksel, JN Wilson, PD Gader - IEEE transactions on neural …, 2012 - ieeexplore.ieee.org
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 …

[图书][B] Data mining with decision trees: theory and applications

OZ Maimon, L Rokach - 2014 - books.google.com
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 …

[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 …

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 …

[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 …

Demystifying softmax gating function in Gaussian mixture of experts

H Nguyen, TT Nguyen, N Ho - Advances in Neural …, 2023 - proceedings.neurips.cc
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 …

[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 …