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spark-nndescent from group info.debatty (version 0.1)

Group: info.debatty Artifact: spark-nndescent
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Artifact spark-nndescent
Group info.debatty
Version 0.1

SMOTE from group nz.ac.waikato.cms.weka (version 1.0.3)

Resamples a dataset by applying the Synthetic Minority Oversampling TEchnique (SMOTE). The original dataset must fit entirely in memory. The amount of SMOTE and number of nearest neighbors may be specified. For more information, see Nitesh V. Chawla et. al. (2002). Synthetic Minority Over-sampling Technique. Journal of Artificial Intelligence Research. 16:321-357.

Group: nz.ac.waikato.cms.weka Artifact: SMOTE
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Artifact SMOTE
Group nz.ac.waikato.cms.weka
Version 1.0.3
Last update 03. April 2013
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/SMOTE
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
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NNge from group nz.ac.waikato.cms.weka (version 1.0.2)

Nearest-neighbor-like algorithm using non-nested generalized exemplars (which are hyperrectangles that can be viewed as if-then rules). For more information, see Brent Martin (1995). Instance-Based learning: Nearest Neighbor With Generalization. Hamilton, New Zealand. Sylvain Roy (2002). Nearest Neighbor With Generalization. Christchurch, New Zealand.

Group: nz.ac.waikato.cms.weka Artifact: NNge
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Artifact NNge
Group nz.ac.waikato.cms.weka
Version 1.0.2
Last update 26. April 2012
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/NNge
License GNU General Public License 3
Dependencies amount 2
Dependencies weka-dev, weka-dev,
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k3nn from group io.github.k3nn (version 0.01)

Group: io.github.k3nn Artifact: k3nn
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Artifact k3nn
Group io.github.k3nn
Version 0.01

voyager from group com.spotify (version 2.1.0)

Group: com.spotify Artifact: voyager
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Artifact voyager
Group com.spotify
Version 2.1.0
Last update 13. December 2024
Organization not specified
URL Not specified
License The Apache Software License, Version 2.0
Dependencies amount 0
Dependencies No dependencies
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hnswlib-jna from group com.stepstone.search.hnswlib.jna (version 1.4.2)

Group: com.stepstone.search.hnswlib.jna Artifact: hnswlib-jna
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Artifact hnswlib-jna
Group com.stepstone.search.hnswlib.jna
Version 1.4.2
Last update 10. February 2021
Organization not specified
URL Not specified
License Apache License, Version 2.0
Dependencies amount 1
Dependencies jna,
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hnswlib-jna-example from group com.stepstone.search.hnswlib.jna.example (version 1.4.2)

Group: com.stepstone.search.hnswlib.jna.example Artifact: hnswlib-jna-example
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Artifact hnswlib-jna-example
Group com.stepstone.search.hnswlib.jna.example
Version 1.4.2
Last update 10. February 2021
Organization not specified
URL Not specified
License Apache License, Version 2.0
Dependencies amount 1
Dependencies hnswlib-jna,
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hnswlib-jna-parent from group com.stepstone.search.hnswlib.jna (version 1.4.2)

This project contains a JNA (Java Native Access) implementation built on top of the native Hnswlib (Hierarchical Navigable Small World Graph) which offers a fast approximate nearest neighbor search. It includes some modifications and simplifications in order to provide Hnswlib features with native like performance to applications written in Java. Differently from the original Python implementation, the multi-thread support is not included in the bindings itself but it can be easily implemented on the Java side.

Group: com.stepstone.search.hnswlib.jna Artifact: hnswlib-jna-parent
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Artifact hnswlib-jna-parent
Group com.stepstone.search.hnswlib.jna
Version 1.4.2
Last update 10. February 2021
Organization not specified
URL https://github.com/stepstone-tech/hnswlib-jna
License Apache License, Version 2.0
Dependencies amount 0
Dependencies No dependencies
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hnswlib-jna-legacy from group com.stepstone.search.hnswlib.jna (version 1.4.2)

Group: com.stepstone.search.hnswlib.jna Artifact: hnswlib-jna-legacy
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Artifact hnswlib-jna-legacy
Group com.stepstone.search.hnswlib.jna
Version 1.4.2

supervisedAttributeScaling from group nz.ac.waikato.cms.weka (version 1.0.2)

Package containing a class that rescales the attributes in a classification problem based on their discriminative power. This is useful as a pre-processing step for learning algorithms such as the k-nearest-neighbour method, to replace simple normalization. Each attribute is rescaled by multiplying it with a learned weight. All attributes excluding the class are assumed to be numeric and missing values are not permitted. To achieve the rescaling, this package also contains an implementation of non-negative logistic regression, which produces a logistic regression model with non-negative weights .

Group: nz.ac.waikato.cms.weka Artifact: supervisedAttributeScaling
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1 downloads

Artifact supervisedAttributeScaling
Group nz.ac.waikato.cms.weka
Version 1.0.2
Last update 30. October 2018
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/supervisedAttributeScaling
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!

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