Sentence examples for maximum likelihood decision from inspiring English sources

A Hybrid Decision Tree (HDT) Classifier was used to combine maximum likelihood decision rules, a brightness differencing technique, and a spatial/contextual rule base.

In particular, the acceptance set can be assigned according to the maximum likelihood decision rule.

The maximum likelihood decision rule is implemented by using the acceptance set (18).

The probabilities introduced above can be easily estimated for, which corresponds to the maximum likelihood decision rule.

To decode, a scalar correlation is computed and the final decision is computed with a maximum likelihood decision rule.

To classify a document, we employ a modified maximum likelihood decision rule, constructed so as to bias the decision towards the safe "mix" classification.

An optimum detector for this communication is proposed based on maximum-likelihood decision.

We propose a maximum-likelihood decision based on the conditional pdf of.

Consequently, we design an optimal detector for multiplicative watermarking based on using the Maximum Likelihood (ML) decision rule and BKF distribution.

Three classification algorithms (maximum likelihood, boosted decision trees, and support vector machines) were tested for their ability to monitor expansion across five time periods (1988 1995, 1996 2000, 2001 2003, 2004 2006, 2007 2009) in three study areas that differ in size, eco-climatic conditions, and rates/patterns of development.

The majority rule and discrete HMM (DHMM) rule accumulate single-frame face recognition results, while continuous density HMM (CDHMM) works directly with the PCA facial features of the video segment for accumulated maximum likelihood (ML) decision.