Data Dimensionality Reduction Framework for Data Mining
نویسندگان
چکیده
منابع مشابه
A Visual Interaction Framework for Dimensionality Reduction Based Data Exploration
Dimensionality reduction is a common method for analyzing and visualizing high-dimensional data. However, reasoning dynamically about the results of a dimensionality reduction is difficult. Dimensionality-reduction algorithms use complex optimizations to reduce the number of dimensions of a dataset, but these new dimensions often lack a clear relation to the initial data dimensions, thus making...
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Dimensionality reduction is one of the basic operations in the toolbox of data-analysts and designers of machine learning and pattern recognition systems. Given a large set of measured variables but few observations, an obvious idea is to reduce the degrees of freedom in the measurements by representing them with a smaller set of more “condensed” variables. Another reason for reducing the dimen...
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A common objective in image analysis is dimensionality reduction. The most common often used data-exploratory technique with this objective is principal component analysis. We propose a new method based on the projection of the images as matrices after a Procrustes rotation and show that it leads to a better reconstruction of images.
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Microarrays are being currently used for the expression levels of thousands of genes simultaneously. They present new analytical challenges because they have a very high input dimension and a very low sample size. It is highly complex to analyse multi-dimensional data with complex geometry and to identify low-dimensional “principal objects” that relate to the optimal projection while losing the...
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Principal Component Analysis ( PCA ), Locally Linear Embedding ( LLE ) and Isomap techniques can be used to process and analyze high-dimensional data domains. These methodologies create low-dimensional embeddings of the original data which are easier to work with than the initial high-dimensional data. The goal of this report is to show how the above methods can be applied to very high-dimensio...
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ژورنال
عنوان ژورنال: Electronics and Electrical Engineering
سال: 2013
ISSN: 2029-5731,1392-1215
DOI: 10.5755/j01.eee.19.4.2043