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Showing Items 91-100 of 664 on page 10 of 67: First Previous 5 6 7 8 9 10 11 12 13 14 15 Next Last

Logo r-cran-arules 1.5-4

by r-cran-robot - October 12, 2017, 00:00:00 CET [ Project Homepage BibTeX Download ] 51048 views, 10261 downloads, 3 subscriptions

About: Mining Association Rules and Frequent Itemsets

Changes:

Fetched by r-cran-robot on 2018-01-01 00:00:03.787534


Logo r-cran-effects 4.0-0

by r-cran-robot - September 14, 2017, 00:00:00 CET [ Project Homepage BibTeX Download ] 1152 views, 295 downloads, 1 subscription

About: Effect Displays for Linear, Generalized Linear, and Other Models

Changes:

Fetched by r-cran-robot on 2018-01-01 00:00:07.810965


Logo JMLR Jstacs 2.3

by keili - September 13, 2017, 14:25:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 33547 views, 7697 downloads, 4 subscriptions

About: A Java framework for statistical analysis and classification of biological sequences

Changes:

New classes and packages:

  • Jstacs 2.3 is the first release to be accompanied by JstacsFX, a library for building JavaFX-based graphical user interfaces based on JstacsTools
  • new interface MultiThreadedFunction
  • new class LargeSequenceReader for reading large sequence files in chunks
  • new interface QuickScanningSequenceScore
  • new class RegExpValidator for checking String inputs against a regular expression
  • new class IUPACDNAAlphabet

New features and improvements:

  • Alignments may now handle different costs for insert and delete gaps
  • ListResults may now be constructed from Collections of ResultSets
  • Several minor improvements and bugfixes in many classes
  • Improvements of documentation of several classes

Logo Spectra. A Library for Large Scale Eigenvalue Problems 0.5.0

by yixuanq - September 13, 2017, 02:34:21 CET [ Project Homepage BibTeX Download ] 897 views, 280 downloads, 2 subscriptions

About: A header-only C++ library for solving large scale eigenvalue problems

Changes:

Initial Announcement on mloss.org.


About: Tool aimed at helping remedy the reproducibility problem, specifically in the statistical and data wrangling aspects.

Changes:

Initial Announcement on mloss.org.


Logo Top Frequency Based Parallel Coordinates 1.0.0

by matloff - September 5, 2017, 05:49:41 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1010 views, 207 downloads, 1 subscription

About: A novel method to create parallel coordinates plots on large data sets without causing a "black screen" problem.

Changes:

Initial Announcement on mloss.org.


Logo python weka wrapper3 0.1.3

by fracpete - August 23, 2017, 01:18:36 CET [ Project Homepage BibTeX Download ] 4799 views, 1064 downloads, 3 subscriptions

About: A thin Python3 wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls.

Changes:
  • added check_for_modified_class_attribute method to FilterClassifier class
  • added complete_classname method to weka.core.classes module, which allows completion of partial classnames like .J48 to weka.classifiers.trees.J48; if there is a unique match; JavaObject.new_instance and JavaObject.check_type now make use of this functionality, allowing for instantiations like Classifier(cls=".J48")
  • jvm.start(system_cp=True) no longer fails with a KeyError: 'CLASSPATH' if there is no CLASSPATH environment variable defined
  • Libraries mtl.jar, core.jar and arpack_combined_all.jar were added as is to the weka.jar in the 3.9.1 release instead of adding their content to it. Repackaged weka.jar to fix this issue.

Logo python weka wrapper 0.3.11

by fracpete - August 23, 2017, 01:17:24 CET [ Project Homepage BibTeX Download ] 57398 views, 11576 downloads, 3 subscriptions

About: A thin Python wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls.

Changes:
  • added check_for_modified_class_attribute method to FilterClassifier class
  • added complete_classname method to weka.core.classes module, which allows completion of partial classnames like .J48 to weka.classifiers.trees.J48; if there is a unique match; JavaObject.new_instance and JavaObject.check_type now make use of this functionality, allowing for instantiations like Classifier(cls=".J48")
  • jvm.start(system_cp=True) no longer fails with a KeyError: 'CLASSPATH' if there is no CLASSPATH environment variable defined
  • Libraries mtl.jar, core.jar and arpack_combined_all.jar were added as is to the weka.jar in the 3.9.1 release instead of adding their content to it. Repackaged weka.jar to fix this issue.

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 r-cran-CORElearn 1.51.2

by r-cran-robot - August 8, 2017, 00:00:00 CET [ Project Homepage BibTeX Download ] 22998 views, 4552 downloads, 2 subscriptions

About: Classification, Regression and Feature Evaluation

Changes:

Fetched by r-cran-robot on 2018-01-01 00:00:07.164852


Showing Items 91-100 of 664 on page 10 of 67: First Previous 5 6 7 8 9 10 11 12 13 14 15 Next Last