Skip to search formSkip to main content
You are currently offline. Some features of the site may not work correctly.

Cluster-weighted modeling

In data mining, cluster-weighted modeling (CWM) is an algorithm-based approach to non-linear prediction of outputs (dependent variables) from inputs… Expand
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2012
Highly Cited
2012
Cluster-weighted modeling (CWM) is a mixture approach to modeling the joint probability of data coming from a heterogeneous… Expand
  • figure 1
  • table 1
  • figure 2
  • figure 3
  • figure 4
Is this relevant?
2012
2012
Cluster-Weighted Modeling (CWM) is a flexible mixture approach for modeling the joint probability of data coming from a… Expand
  • table 1
  • table 2
  • figure 1
  • figure 2
  • figure 3
Is this relevant?
2010
2010
We consider Cluster-Weighted Modeling in order to model functional dependence between some input and output variables  based on… Expand
Is this relevant?
2009
2009
We investigate statistical properties of Cluster-Weighted Modeling, which is a framework for supervised learning originally… Expand
Is this relevant?
2007
2007
Aside from the Expectation-Maximization (EM) algorithm, Least-Mean-Square (LMS) is devised to further train the model parameters… Expand
Is this relevant?
2005
2005
The cluster-weighted modeling (CWM) is a mixture density estimator around local models. To be specific, the input regions… Expand
  • table I
  • table II
  • table III
Is this relevant?
2001
2001
We discuss an approach to joint density estimation called cluster-weighted modeling (CWM). The base approach was originally… Expand
  • figure 1
  • figure 2
  • figure 3
Is this relevant?
2001
2001
Cluster-weighted modeling (CWM) was proposed by Gershenfeld (1999) for density estimation in joint input-output space. In the… Expand
  • figure 1
  • figure 2
  • figure 3
  • figure 4
Is this relevant?
2001
2001
Cluster-weighted modeling, a mixture density estimator around local models, is presented as a framework for the analysis… Expand
Is this relevant?
1999
1999
We present a framework for the analysis and synthesis of acoustical instruments based on data-driven probabilistic inference… Expand
Is this relevant?