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Quantum-like Gaussian mixture model
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DOI：10.1007/s00500-021-05941-9.png)
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Abstract
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A new concept of a quantum-like mixture model is introduced. It describes the mixture distribution with the assumption that a point is generated by each Gaussian at the same time. The quantum-like mixture Gaussian improves the classification accuracy in machine learning by indicating that the uncertain points should not be assigned to any class. It increases the accuracy of the mixture Gaussian model on the iris data set from 96.67 to 99.24%.
Keywords:
Clustering
Quantum probabilities
Interference
Gaussian mixture model
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