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About: A non-iterative, incremental and hyperparameter-free learning method for one-layer feedforward neural networks without hidden layers. This method efficiently obtains the optimal parameters of the network, regardless of whether the data contains a greater number of samples than variables or vice versa. It does this by using a square loss function that measures errors before the output activation functions and scales them by the slope of these functions at each data point. The outcome is a system of linear equations that obtain the network's weights and that is further transformed using Singular Value Decomposition.

Changes:

Initial Announcement on mloss.org.


Logo KeLP 2.2.1

by kelpadmin - August 7, 2017, 17:20:39 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 16880 views, 3633 downloads, 3 subscriptions

About: Kernel-based Learning Platform (KeLP) is Java framework that supports the implementation of kernel-based learning algorithms, as well as an agile definition of kernel functions over generic data representation, e.g. vectorial data or discrete structures. The framework has been designed to decouple kernel functions and learning algorithms, through the definition of specific interfaces. Once a new kernel function has been implemented, it can be automatically adopted in all the available kernel-machine algorithms. KeLP includes different Online and Batch Learning algorithms for Classification, Regression and Clustering, as well as several Kernel functions, ranging from vector-based to structural kernels. It allows to build complex kernel machine based systems, leveraging on JSON/XML interfaces to instantiate prediction models without writing a single line of code.

Changes:

In addition to minor bug fixes, this release includes:

  • A new cache (FixSizeKernelCache) that can store a larger number of computations.

  • Evaluators for measuring the quality of Clustering algorithms.

Furthermore we also released the new module kelp-input-generator, that contains the facilities to parse text snippets and generate tree representations for KeLP!

Check out this new version from our repositories. API Javadoc is already available. Your suggestions will be very precious for us, so download and try KeLP 2.2.1!


About: A non-iterative learning method for one-layer (no hidden layer) neural networks, where the weights can be calculated in a closed-form manner, thereby avoiding low convergence rate and also hyperparameter tuning. The proposed learning method, LANN-SVD in short, presents a good computational efficiency for large-scale data analytic.

Changes:

Initial Announcement on mloss.org.


About: An open-source framework for benchmarking of feature selection algorithms and cost functions.

Changes:

Initial Announcement on mloss.org.


Logo pSpectralClustering 1.2

by tbuehler - July 30, 2017, 20:07:52 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 10656 views, 2256 downloads, 2 subscriptions

About: A generalized version of spectral clustering using the graph p-Laplacian.

Changes:

various internal optimizations


Logo KeBABS 1.5.4

by UBod - July 28, 2017, 09:55:04 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 19730 views, 3614 downloads, 3 subscriptions

About: Kernel-Based Analysis of Biological Sequences

Changes:
  • importing apcluster package for avoiding method clashes
  • improved and completed change history in inst/NEWS and package vignette

Logo APCluster 1.4.4

by UBod - July 28, 2017, 09:47:32 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 44322 views, 7466 downloads, 3 subscriptions

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About: The apcluster package implements Frey's and Dueck's Affinity Propagation clustering in R. The package further provides leveraged affinity propagation, exemplar-based agglomerative clustering, and various tools for visual analysis of clustering results.

Changes:
  • changed dependency to suggested package 'kebabs' to version of at least 1.5.4 for improved interoperability
  • bug fix in as.dendrogram() method with signature 'AggExResult'
  • added discrepancy metric to distance computations and updated src/distanceL.c to new version
  • registered C/C++ subroutines
  • minor change in the vignette template
  • moved NEWS to inst/NEWS
  • added inst/COPYRIGHT

Logo HyperStream 0.3.6

by tdiethe - July 27, 2017, 04:11:57 CET [ Project Homepage BibTeX Download ] 661 views, 119 downloads, 1 subscription

About: Hyperstream is a large-scale, flexible and robust software package for processing streaming data.

Changes:

python 3 support; new API; bug fixes and enhancements


About: pycobra is a python library for ensemble learning, which serves as a toolkit for regression, classification, and visualisation. It is scikit-learn compatible and fits into the existing scikit-learn ecosystem.

Changes:

Project is now fully scikit-learn compatible, implements 2 new predictor aggregation algorithms, more Jupyter notebooks and examples, and continuous integration for tests.


Logo JMLR MLPACK 2.2.4

by rcurtin - July 19, 2017, 04:24:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 85025 views, 15212 downloads, 6 subscriptions

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About: A scalable, fast C++ machine learning library, with emphasis on usability.

Changes:

Released July 18, 2017.

  • Speed and memory improvements for DBSCAN. --single_mode can now be used for situations where previously RAM usage was too high.

  • Fix bug in CF causing incorrect recommendations.


Showing Items 1-10 of 648 on page 1 of 65: 1 2 3 4 5 6 Next Last