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algorithms from group de.cit-ec.tcs.alignment (version 3.1.1)
This module defines the interface for AlignmentAlgorithms as well as some helper classes. An
AlignmentAlgorithm computes an Alignment of two given input sequences, given a Comparator that
works in these sequences.
More details on the AlignmentAlgorithm can be found in the respective interface. More information
on Comparators can be found in the comparators module.
The resulting 'Alignment' may be just a real-valued dissimilarity between the input sequence or
may incorporate additional information, such as a full Alignment, a PathList, a PathMap or a
CooptimalModel. If those results support the calculation of a Gradient, they implement the
DerivableAlignmentDistance interface.
In more detail, the Alignment class represents the result of a backtracing scheme, listing all
Operations that have been applied in one co-optimal Alignment.
A classic AlignmentAlgorithm does not result in a differentiable dissimilarity, because the
minimum function is not differentiable. Therefore, this package also contains utility functions
for a soft approximation of the minimum function, namely Softmin.
For faster (parallel) computation of many different alignments or gradients we also provide the
ParallelProcessingEngine, the SquareParallelProcessingEngine and the ParallelGradientEngine.
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Artifact algorithms
Group de.cit-ec.tcs.alignment
Version 3.1.1
Last update 26. October 2018
Organization not specified
URL http://openresearch.cit-ec.de/projects/tcs
License The GNU Affero General Public License, Version 3
Dependencies amount 3
Dependencies comparators, parallel, lombok,
There are maybe transitive dependencies!
Group de.cit-ec.tcs.alignment
Version 3.1.1
Last update 26. October 2018
Organization not specified
URL http://openresearch.cit-ec.de/projects/tcs
License The GNU Affero General Public License, Version 3
Dependencies amount 3
Dependencies comparators, parallel, lombok,
There are maybe transitive dependencies!
comparators from group de.cit-ec.tcs.alignment (version 3.1.1)
This module defines the interfaces for Comparators in the TCS Alignment Toolbox. A Comparator has
the purpose of defining the dissimilarity between elements in the input sequences of an
Alignment. More specific information on Comparators can be found in the 'Comparator' interface.
You can find a lot of helpful standard implementations of Comparators in the comparators-lib
module.
In the TCS Alignment Toolbox we require the output values of Comparators to lie in the range
[0,1]. Many natural dissimilarities on value sets do not meet this criterion, such that
additional normalization has to be applied. To that end this package also contains a Normalizer
interface for functions that map real values from the range [0, infinity) to the range [0,1].
This package also provides a few convenience implementations of the Comparator interface to make
the implementation of custom Comparators simpler, namely: SkipExtendedComparator,
ParameterLessSkipExtendedComparator, ComparisonBasedSkipExtendedComparator, and
ParameterLessComparisonBasedSkipExtendedComparator.
Finally the TCS Alignment Toolbox also provides the means to learn parameters of Comparators. To
enable that Comparators must implement the DerivableComparator interface to properly define the
parameters that can be learned and the gradient of the dissimilarity with respect to these
parameters. Gradients are stored using the Gradient interface as well as some convenience
implementations of said interface, namely EmptyGradient, SingletonGradient, ArrayGradient and
ListGradient.
Group: de.cit-ec.tcs.alignment Artifact: comparators
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Artifact comparators
Group de.cit-ec.tcs.alignment
Version 3.1.1
Last update 26. October 2018
Organization not specified
URL http://openresearch.cit-ec.de/projects/tcs
License The GNU Affero General Public License, Version 3
Dependencies amount 1
Dependencies lombok,
There are maybe transitive dependencies!
Group de.cit-ec.tcs.alignment
Version 3.1.1
Last update 26. October 2018
Organization not specified
URL http://openresearch.cit-ec.de/projects/tcs
License The GNU Affero General Public License, Version 3
Dependencies amount 1
Dependencies lombok,
There are maybe transitive dependencies!
rng from group de.cit-ec.ml (version 1.0.0)
This is an implementation of the Neural Gas algorithm on
distance data (Relational Neural Gas) for unsupervised clustering.
We recommend that you use the functions provided by the RelationalNeuralGas
class for your purposes. All other classes and functions are utilities which
are used by this central class. In particular, you can use RelationalNeuralGas.train()
to obtain a RNGModel (i.e. a clustering of your data), and subsequently
you can use RelationalNeuralGas.getAssignments() to obtain the resulting
cluster assignments, and RelationalNeuralGas.classify() to cluster new points
which are not part of the training data set.
The underlying scientific work is summarized nicely in the dissertation
"Topographic Mapping of Dissimilarity Datasets" by Alexander Hasenfuss
(2009).
The basic properties of an Relational Neural Gas algorithm are the following:
1.) It is relational: The data is represented only in terms of a pairwise
distance matrix.
2.) It is a clustering method: The algorithm provides a clustering model,
that is: After calculation,
each data point should be assigned to a cluster (for this package here we
only consider hard clustering, that is: each data point is assigned to
exactly one cluster).
3.) It is a vector quantization method: Each cluster corresponds to a
prototype, which is in the center of the
cluster and data points are assigned to the cluster if and only if they are
closest to this particular prototype.
4.) It is rank-based: The updates of the prototypes depend only on
the distance ranking, not on the absolute value of the distances.
Artifact rng
Group de.cit-ec.ml
Version 1.0.0
Last update 26. January 2018
Organization not specified
URL https://gitlab.ub.uni-bielefeld.de/bpaassen/relational_neural_gas
License The GNU General Public License, Version 3
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
Group de.cit-ec.ml
Version 1.0.0
Last update 26. January 2018
Organization not specified
URL https://gitlab.ub.uni-bielefeld.de/bpaassen/relational_neural_gas
License The GNU General Public License, Version 3
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!
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