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Showing Items 101-110 of 598 on page 11 of 60: First Previous 6 7 8 9 10 11 12 13 14 15 16 Next Last

Logo LMW Tree 1.0

by cdevries - May 30, 2015, 11:42:23 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1018 views, 193 downloads, 2 subscriptions

About: Learning M-Way Tree - Web Scale Clustering - EM-tree, K-tree, k-means, TSVQ, repeated k-means, clustering, random projections, random indexing, hashing, bit signatures


Initial Announcement on

Logo ABACOC Adaptive Ball Cover for Classification 2.0

by kikot - May 29, 2015, 11:57:28 CET [ BibTeX BibTeX for corresponding Paper Download ] 2746 views, 678 downloads, 3 subscriptions

About: Incremental (Online) Nonparametric Classifier. You can classify both points (standard) or matrices (multivariate time series). Java and Matlab code already available.


version 2: parameterless system, constant model size, prediction confidence (for active learning).

NEW!! C++ version at:

Logo Probabilistic Classification Vector Machine 0.21

by fmschleif - May 26, 2015, 16:24:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2071 views, 493 downloads, 3 subscriptions

About: PCVM library a c++/armadillo implementation of the Probabilistic Classification Vector Machine.


27.05.2015: - Matlab binding under Windows available. Added a solution file for VS'2013 express to compile a matlab mex binding. Can not yet confirm that under windows the code is really using multiple cores (under linux it does)

Logo KeBABS 1.2.3

by UBod - May 26, 2015, 10:55:44 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6139 views, 1078 downloads, 3 subscriptions

About: Kernel-Based Analysis of Biological Sequences

  • new export kebabsCollectInfo for collection of package info
  • update of version dependency to Biostrings, XVector, S4Vector
  • correction for leading + or - in factor label
  • change of bibtex style sheet in vignette to plainnat.bst

About: Jie Gui et al., "How to estimate the regularization parameter for spectral regression discriminant analysis and its kernel version?", IEEE Transactions on Circuits and Systems for Video Technology, vol. 24, no. 2, pp. 211-223, 2014


Initial Announcement on

About: Jie Gui, Zhenan Sun, Guangqi Hou, Tieniu Tan, "An optimal set of code words and correntropy for rotated least squares regression", International Joint Conference on Biometrics, 2014, pp. 1-6


Initial Announcement on

Logo ClusterEval 1.1

by cdevries - May 18, 2015, 22:01:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3591 views, 951 downloads, 2 subscriptions

About: Cluster quality Evaluation software. Implements cluster quality metrics based on ground truths such as Purity, Entropy, Negentropy, F1 and NMI. It includes a novel approach to correct for pathological or ineffective clusterings called 'Divergence from a Random Baseline'.


Moved project to GitHub.

Logo GESL v1.01

by bellet - May 15, 2015, 11:54:04 CET [ BibTeX BibTeX for corresponding Paper Download ] 1961 views, 783 downloads, 1 subscription

About: Learning string edit distance / similarity from data


Added datasets used in the experiments of the paper

Logo Cognitive Foundry 3.4.1

by Baz - May 13, 2015, 06:55:24 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 21826 views, 3606 downloads, 3 subscriptions

About: The Cognitive Foundry is a modular Java software library of machine learning components and algorithms designed for research and applications.

  • General:
    • Updated MTJ to version 1.0.2 and netlib-java to 1.1.2.
    • Updated XStream to version 1.4.8.
  • Common:
    • Fixed issue in VectorUnionIterator.
  • Learning:
    • Added Alternating Least Squares (ALS) Factorization Machine training implementation.
    • Fixed performance issue in Factorization Machine where linear component was not making use of sparsity.
    • Added utility function to sigmoid unit.

Logo XGBoost v0.4.0

by crowwork - May 12, 2015, 08:57:16 CET [ Project Homepage BibTeX Download ] 9107 views, 1783 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

  • 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 101-110 of 598 on page 11 of 60: First Previous 6 7 8 9 10 11 12 13 14 15 16 Next Last