Dear Mr. Naik,
UVQ is short for Unsupervised Vector Quantizer. The supervised version of UVQ is called LVQ (Linear Vector Quantizer). This model is not supported in OpendTect.
In the old Neural Networks plugin, which is nowadays launched from the ML control Center, you can do a nonlinear supervised waveform classification with a Multi-Layer-Perceptron. The workflow is as follows:
- Create pointsets for all N classes
- Create an attribute set that extracts wavelet samples (Open the Default Attribute Set: "Workflow - Unsupervised Waveform Segmentation")
- Open the Neural Networks plugin from the ML control center
- Select Pattern Recognition (Pointsets ...)
- Select Supervised, Input the waveform attributes, output the N pointsets
- Train and Apply
Alternative linear and nonlinear classifications are possible in the Machine Learning plugin. A linear classification can be done with a Support Vector Machine (SVM). This is a model in Scikit Learn in the new Machine Learning plugin. A SVM classifies the data by constructing hyperplanes in data space. If you select the linear kernel, the hyperplane will be a linear plane. The workflow for this is:
- Create pointsets for all N classes
- Select the "Seismic Classification (Supervised)" workflow from the Seismic tab in the ML control center
- Select all pointsets as inputs
- Select the waveform from the input seismic
- Select Scikit Learn as Machine Learning Platform
- Select Type SVM (Support Vector Model) and kernel is Linear
- Train and Apply
Best regards,
Paul.
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Paul de Groot
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