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Contents
- Article
Overview
1. Dimensionality Reduction 2. Gaussian Process 3. Gaussian Process Latent Variable Model
- Article
WIKIPEDIA ARTICLE GROUP 9 Contents Article Overview 1. - - PowerPoint PPT Presentation
WIKIPEDIA ARTICLE GROUP 9 Contents Article Overview 1. - - PowerPoint PPT Presentation
WIKIPEDIA ARTICLE GROUP 9 Contents Article Overview 1. Dimensionality Reduction 2. Gaussian Process 3. Gaussian Process Latent Variable Model Article Edits Dimensionality Reduction According to dimensionality reduction
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Dimensionality Reduction
According to dimensionality reduction , data
- f
interest lie
- n
an embedded non-linear manifold within the higher-dimensional
- space. If
the manifold is
- f
low enough dimension, the data can be visualised in the low-dimensional space.(wikipedia)
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Dimensionality Reduction
A simple model of the digit – rotate the ‘prototype’.
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Dimensionality Reduction
Projection onto Principal Components.
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20 40 60
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20 40 60 PC no 2 PC no 3
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Gaussian Process
- Distribution
- ver
functions
- f
infinite dimensions defined by the mean and covariance.
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Gaussian Process Latent Variable Model
- Gaussian
Process Latent Variable Model is a technique from dimensionality reduction which has the essence
- f
both Gaussian processes and dimensionality Reduction Techniques.
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Gaussian Process Latent Variable Model
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Proposed Article Edits
- Added
relevant images to the article to make the description more intutive and appealing.
- Added
references and links to relevant material for technical terms used in the article.
- Simplified
the language , providing a more intutive explanation
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various non technical terms used as a part
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the article
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