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In general, conventional analysis for high-dimensional

In general, conventional analysis for high-dimensional J3q2w

In general, conventional analysis for high-dimensional chemical data may be divided into two distinct families: clustering and classification. Clustering strategies are seeking to describe a data set in groups of related objectives. Clusters are defined via determining how individual measurements relate to each other using some kind of optimized distance criterion (e. g. , nearest neighbor, minimizing cluster variance). classification methods, alternatively, try to predict data about an unknown sample based on previously obtained data. each method is typically optimized for one task and not for the other. Analytical methods can be supervised, in which case the evaluation algorithm consists of information about known individual samples and is forced to treat them in the same way, or unsupervised, wherein all cases are evaluated equally, with out external information.

In general
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data
 may be divided
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describe
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data
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classification
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data
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data
. This sentence does not start with an uppercase letterEach
each
 method is typically
 optimized for one task and not for the other. Analytical methods can be supervised
, in which case the evaluation algorithm consists of information about known individual samples and is forced
 to treat them in the same way
, or unsupervised, wherein all cases are evaluated
equally
, This word is usually written together. Did you mean "without"?without
with out
 external information. 