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Keyword: Gaussian Mixture Model
Acoustic Scene Classifier Based on Gaussian Mixture Model in the Concept Drift Situation
The data distribution used in model training is assumed to be similar with that when the model is applied. However, in some applications, data distributions may change over time. This situation is called the concept drift, which might decrease the model performance because the model is trained and evaluated in different distributions. To solve this…
Read More Cancer Mediating Genes Recognition using Multilayer Perceptron Model- An Application on Human Leukemia
In the present article, we develop multilayer perceptron model for identification of some possible genes mediating different leukemia. The procedure involves grouping of gene based correlation coefficient and finally select of some possible genes. The procedure has been successfully applied three human leukemia gene expression data sets. The superiority of the procedure has been demonstrated…
Read More Empirical Probability Distributions with Unknown Number of Components
We consider the estimation of empirical probability distributions, both discrete and continuous. We focus on deriving formulas to estimate number of categories for the discrete distribution, when the number of categories is hidden, and the means and methods to estimate the number of components in the Gaussian mixture model representing a probability density function given…
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