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In statistics, a mixture model is a probabilistic model for representing the presence of subpopulations within an overall population, without requiring that an observed data set should identify the sub-population to which an individual observation belongs. Formally a mixture model corresponds to the mixture distribution that represents the probability…
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mixture model models gaussian distributions parameters distribution data one em normal used components different component example set values random image
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Mixture model | is a | probabilistic model for representing the presence of subpopulations within an overall population | 0.90 | text |
| Mixture model | is a | hierarchical model consisting of the following components | 0.90 | text |
| prices or incomes that are guaranteed to be positive | instance of | Note that for values | 0.80 | text |
| which tend to grow exponentially | instance of | Note that for values | 0.80 | text |
| a log-normal distribution might actually be a better model than a normal distribution | instance of | Note that for values | 0.80 | text |
| spectral analysis | instance of | Each formed cluster can be diagnosed using techniques | 0.80 | text |
| early fault detection.Fuzzy image segmentationIn image processing | instance of | this has also been widely used in other areas | 0.80 | text |
| computer vision | instance of | this has also been widely used in other areas | 0.80 | text |
| traditional image segmentation models often assign to one pixel only one exclusive pattern | instance of | this has also been widely used in other areas | 0.80 | text |
| Gaussian mixture models | instance of | such spatially regularized mixture models could lead to more realistic and computationally efficient segmentation methods.Point set registrationProbabilistic mixture models | 0.80 | text |
| early fault detection | instance of | this has also been widely used in other areas | 0.80 | text |
| Gaussian mixture models | instance of | Point set registrationProbabilistic mixture models | 0.80 | text |
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