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Logo r-cran-svmpath 0.952

by r-cran-robot - February 1, 2012, 00:00:11 CET [ Project Homepage BibTeX Download ] 12462 views, 2614 downloads, 1 subscription

About: svmpath

Changes:

Fetched by r-cran-robot on 2012-02-01 00:00:11.755984


Logo r-cran-CORElearn 1.47.1

by r-cran-robot - September 3, 2015, 00:00:00 CET [ Project Homepage BibTeX Download ] 11504 views, 2598 downloads, 0 subscriptions

About: Classification, Regression and Feature Evaluation

Changes:

Fetched by r-cran-robot on 2016-06-01 00:00:05.529637


Logo chi2 kernel 1.5

by gruel - February 15, 2009, 22:32:21 CET [ BibTeX Download ] 13195 views, 2591 downloads, 1 subscription

About: Very fast implementation of the chi-squared distance between histograms (or vectors with non-negative entries).

Changes:

Removed bug in symmetric chi-square distance and updated python wrapper to python 2.5 compatiblity.


Logo PyML a python machine learning library focused on kernel methods 0.7.0

by asa - May 29, 2008, 22:23:39 CET [ Project Homepage BibTeX Download ] 9737 views, 2553 downloads, 0 comments, 0 subscriptions

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About: PyML is an interactive object oriented framework for machine learning in python with a focus on kernel methods.

Changes:

Initial Announcement on mloss.org.


Logo kernlab 0.9-9

by alexis - November 2, 2009, 16:03:50 CET [ Project Homepage BibTeX Download ] 12406 views, 2546 downloads, 0 subscriptions

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About: kernlab provides kernel-based Machine Learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods kernlab [...]

Changes:

minor fixes in kcca and ksvm functions


About: TinyOS is a small operating for small (wireless) sensors. LEGO MINDSTORMS NXT is a platform for embedded systems experimentation: The combination of NXT and TinyOS is NXTMOTE.

Changes:

Initial Announcement on mloss.org.


Logo monte python 0.1.0

by roro - May 9, 2008, 21:45:47 CET [ Project Homepage BibTeX Download ] 6550 views, 2489 downloads, 1 subscription

About: Monte (python) is a small machine learning library written in pure Python. The focus is on gradient based learning, in particular on the construction of complex models from many smaller components.

Changes:

Initial Announcement on mloss.org.


About: Nimfa is an open-source Python library that provides a unified interface to nonnegative matrix factorization algorithms. It includes implementations of state-of-the-art factorization methods, initialization approaches, and quality scoring. Both dense and sparse matrix representation are supported.

Changes:

Initial Announcement on mloss.org.


Logo KReator 1.2.3198

by mthimm - December 23, 2010, 12:07:25 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 11287 views, 2469 downloads, 1 subscription

About: KReator is an integrated development environment (IDE) for relational probabilistic knowledge representation languages. At the moment, KReator supports Bayesian Logic Programs (BLPs), Markov Logic Networks (MLNs), Relational Maximum Entropy (RME), Relational Bayesian Networks (RBN), and Probabilistic Prolog (ProbLog).

Changes:
  • several bugfixes
  • Beta version of ProbLog plugin
  • enhanced command completion in console
  • enhanced error messages for syntax errors
  • refactored logic libraries
  • added prettyprint function in console
  • added syntax highlighting for RBNs

Logo XGBoost v0.4.0

by crowwork - May 12, 2015, 08:57:16 CET [ Project Homepage BibTeX Download ] 13296 views, 2449 downloads, 3 subscriptions

About: xgboost: eXtreme Gradient Boosting It is an efficient and scalable implementation of gradient boosting framework. The package includes efficient linear model solver and tree learning algorithm. The package can automatically do parallel computation with OpenMP, and it can be more than 10 times faster than existing gradient boosting packages such as gbm or sklearn.GBM . It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that user are also allowed to define there own objectives easily. The newest version of xgboost now supports distributed learning on various platforms such as hadoop, mpi and scales to even larger problems

Changes:
  • Distributed version of xgboost that runs on YARN, scales to billions of examples

  • Direct save/load data and model from/to S3 and HDFS

  • Feature importance visualization in R module, by Michael Benesty

  • Predict leaf index

  • Poisson regression for counts data

  • Early stopping option in training

  • Native save load support in R and python

  • xgboost models now can be saved using save/load in R

  • xgboost python model is now pickable

  • sklearn wrapper is supported in python module

  • Experimental External memory version


Showing Items 121-130 of 622 on page 13 of 63: First Previous 8 9 10 11 12 13 14 15 16 17 18 Next Last