Please use this identifier to cite or link to this item:
http://dx.doi.org/10.18419/opus-12023
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Debnath, Munmun | - |
dc.date.accessioned | 2022-03-15T16:02:54Z | - |
dc.date.available | 2022-03-15T16:02:54Z | - |
dc.date.issued | 2021 | de |
dc.identifier.other | 1797743341 | - |
dc.identifier.uri | http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-120401 | de |
dc.identifier.uri | http://elib.uni-stuttgart.de/handle/11682/12040 | - |
dc.identifier.uri | http://dx.doi.org/10.18419/opus-12023 | - |
dc.description.abstract | Dimensionality reduction techniques play a key role in data visualization and analysis, as these techniques project high-dimensional data in low-dimensional space by preserving critical information about the data in low-dimensional space. Dimensionality reduction techniques may suffer from various drawbacks, e.g., many dimensionality reduction techniques are missing a natural out-of-sample extension, i.e., the ability to insert additional data points into an existing projection. Therefore when a data set grows and new data points are introduced, the projection has to be recalculated, which often cannot be well related to the previous projection. This thesis proposes a technique based on kernel PCA to reproduce and update the result of dimensionality reduction techniques to overcome the stated problems with better run-time performance. The proposed technique uses an initial projection provided by an arbitrary dimensionality reduction technique as a template of the embedding space. A corresponding kernel matrix is then approximated to project out-of-sample instances. The approach is evaluated on several datasets for reproduction of projections of different dimensionality reduction techniques. It is shown that the proposed technique provides a coherent projection for out-of-sample data, and has a better run-time performance than several other dimensionality reduction techniques. | en |
dc.language.iso | en | de |
dc.rights | info:eu-repo/semantics/openAccess | de |
dc.subject.ddc | 004 | de |
dc.title | Reproducing, extending and updating dimensionalty reductions | en |
dc.type | masterThesis | de |
ubs.fakultaet | Zentrale Einrichtungen | de |
ubs.institut | Visualisierungsinstitut der Universität Stuttgart | de |
ubs.publikation.seiten | 58 | de |
ubs.publikation.typ | Abschlussarbeit (Master) | de |
Appears in Collections: | 13 Zentrale Universitätseinrichtungen |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Debnath, Munmun.pdf | 2,13 MB | Adobe PDF | View/Open |
Items in OPUS are protected by copyright, with all rights reserved, unless otherwise indicated.