Features are defined such that they focus on isolated aspects of objects. They may neglect other relevant aspects, leading to class overlap. Pixels in images describe everything but pixel-based vector spaces tear the objects apart because their structure is not consciously encoded in the representation. Structural descriptions are rich and describe the structure well, yet they…

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In the recent PRTools updates of September 2012 (4.2.2) November 2012 (4.2.3) and January 2013 (4.2.4) a number of tools have been added and changed of which not everybody might be aware. Here we will pay more attention to them and give some background information about their use. It concerns some new classifiers, the handling…

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Non-Euclidean dissimilarities may arise naturally when we want to build a measure that incorporates important knowledge about the objects. This is fine, but how to embed such dissimilarities in a vector space if we want to use the standard linear algebra tools for generalization? Here the so-called pseudo-Euclidean vector space will be discussed. To understand…

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Dissimilarities measures may be defined as distances in an Euclidean space or such that they can be interpreted as the Euclidean distances. The Euclidean distances satisfy the triangle inequality: the direct distance between two points is smaller than any detour. They are thereby metric. Euclidean Assume we are given a set of pairwise dissimilarities between…

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Dissimilarities have the advantage over features that they potentially consider the entire objects and thereby may avoid class overlap. Dissimilarities have the advantage over pixels that they potentially consider the objects as connected totalities, where pixels tear them apart in thousands of pieces. Consequently, the use of dissimilarities may result in better classification performances…

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It has been argued that dissimilarities are potentially be a good alternative for features. How to build a  good representation will be discussed later. Here the question will be faced: what is a good measure? What type of measurement device should be used? What properties do we demand? If features are given or can be…

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In previous posts the usage of features and pixels is discussed for representing objects in numerical ways. Pros and cons are sketched. Here, a third alternative will be considered: the direct use of dissimilarities. First, we summarize  the conclusions on the use of features and pixels. Features are well suited to represent objects by numbers…

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The pixel representation in its broadest sense samples the objects and uses them to build a vector space. If the sampling is sufficiently dense, it covers everything. How can we loose information? What is wrong? Let us take an image and sample it as on the left above. The pixels can now be ordered as…

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In science knowledge grows from new observations. Pattern recognition aims to contribute to this process in a systematic way. How is this organized in PRTools? What are the building blocks and how are they glued together? Do they constitute a sprawl or an interesting castle?             The most simple place…

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Scientists should build their own instruments. Or at least, be able to open, investigate and understand the tools they are using. If, however, the tools are provided as a black box there should be a manual or literature available that fully explains the ins and outs. In principle, scientists should be able to create their…

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