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| name | Creating model for audio data by using cascade windowing.pdf |
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| name | Creating model for audio data by using cascade windowing.pdf |
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This page shows how to create a model by using Cascade Windowing.
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Significant Features are used to train and optimize a model that creates a prediction for every 3 sec. of the audio data frame. The figure below shows a simple model structure. Each color represents a different class. The neurons (squares) with the same color show how specific data groups occupy the solution spaces. Each small circle represents a significant feature vector. When the location of the unknow vector fall in the influence field of a neuron, the model creates a prediction with the label of the neuron.
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| name | Creating model for audio data by using cascade windowing.pdf |
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| name | Creating model for audio data by using cascade windowing .ipynb |
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| name | Cascade Windowing.pptx |
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