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GClasses
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This uses graph-cut to divide the data into two clusters. It then trains a linear regression model for each cluster to map from inputs to change-in-state. It then aligns the smaller cluster with the larger one such that the linear models are in agreement (as much as possible). More...
#include <GManifold.h>
Public Member Functions | |
| GDynamicSystemStateAligner (size_t neighbors, GMatrix &inputs, GRand &rand) | |
| virtual | ~GDynamicSystemStateAligner () |
| virtual GMatrix * | reduce (const GMatrix &in) |
| Perform the transformation. More... | |
| void | setSeeds (size_t a, size_t b) |
| Specify the source and sink points for dividing the data into two clusters. More... | |
Public Member Functions inherited from GClasses::GTransform | |
| GTransform () | |
| GTransform (GDomNode *pNode, GLearnerLoader &ll) | |
| virtual | ~GTransform () |
Static Public Member Functions | |
| static void | test () |
Protected Attributes | |
| GMatrix & | m_inputs |
| size_t | m_neighbors |
| double * | m_pDistances |
| size_t * | m_pNeighbors |
| GRand & | m_rand |
| size_t | m_seedA |
| size_t | m_seedB |
Additional Inherited Members | |
Protected Member Functions inherited from GClasses::GTransform | |
| virtual GDomNode * | baseDomNode (GDom *pDoc, const char *szClassName) const |
| Child classes should use this in their implementation of serialize. More... | |
This uses graph-cut to divide the data into two clusters. It then trains a linear regression model for each cluster to map from inputs to change-in-state. It then aligns the smaller cluster with the larger one such that the linear models are in agreement (as much as possible).
| GClasses::GDynamicSystemStateAligner::GDynamicSystemStateAligner | ( | size_t | neighbors, |
| GMatrix & | inputs, | ||
| GRand & | rand | ||
| ) |
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Perform the transformation.
Implements GClasses::GTransform.
| void GClasses::GDynamicSystemStateAligner::setSeeds | ( | size_t | a, |
| size_t | b | ||
| ) |
Specify the source and sink points for dividing the data into two clusters.
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