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Logo JMLR BudgetedSVM v1.1

by nemanja - February 12, 2014, 20:53:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5022 views, 903 downloads, 1 subscription

About: BudgetedSVM is an open-source C++ toolbox for scalable non-linear classification. The toolbox can be seen as a missing link between LibLinear and LibSVM, combining the efficiency of linear with the accuracy of kernel SVM. We provide an Application Programming Interface for efficient training and testing of non-linear classifiers, supported by data structures designed for handling data which cannot fit in memory. We also provide command-line and Matlab interfaces, providing users with an efficient, easy-to-use tool for large-scale non-linear classification.

Changes:

Changed license from LGPL v3 to Modified BSD.


Logo CXXNET 0.1

by antinucleon - April 10, 2014, 02:47:08 CET [ Project Homepage BibTeX Download ] 3735 views, 893 downloads, 1 subscription

About: CXXNET (spelled as: C plus plus net) is a neural network toolkit build on mshadow(https://github.com/tqchen/mshadow). It is yet another implementation of (convolutional) neural network. It is in C++, with about 1000 lines of network layer implementations, easily configuration via config file, and can get the state of art performance.

Changes:

Initial Announcement on mloss.org.


Logo MLlib 0.8

by atalwalkar - October 10, 2013, 00:56:25 CET [ Project Homepage BibTeX Download ] 4606 views, 890 downloads, 1 subscription

About: MLlib provides a distributed machine learning (ML) library to address the growing need for scalable ML. MLlib is developed in Spark (http://spark.incubator.apache.org/), a cluster computing system designed for iterative computation. Moreover, it is a component of a larger system called MLbase (www.mlbase.org) that aims to provide user-friendly distributed ML functionality both for ML researchers and domain experts. MLlib currently consists of scalable implementations of algorithms for classification, regression, collaborative filtering and clustering.

Changes:

Initial Announcement on mloss.org.


Logo OpenCV Based Extended Kalman Filter Frame 1.0.0

by openpr_nlpr - December 2, 2011, 05:23:56 CET [ Project Homepage BibTeX Download ] 3328 views, 888 downloads, 1 subscription

About: A simple and clear OpenCV based extended Kalman filter(EKF) abstract class implementation,absolutely following standard EKF equations. Special thanks to the open source project of KFilter1.3. It is easy to inherit it to implement a variable state and measurement EKF for computer vision and INS usages.

Changes:

Initial Announcement on mloss.org.


About: In this paper, we propose an improved principal component analysis based on maximum entropy (MaxEnt) preservation, called MaxEnt-PCA, which is derived from a Parzen window estimation of Renyi’s quadratic entropy. Instead of minimizing the reconstruction error either based on L2-norm or L1-norm, the MaxEnt-PCA attempts to preserve as much as possible the uncertainty information of the data measured by entropy. The optimal solution of MaxEnt-PCA consists of the eigenvectors of a Laplacian probability matrix corresponding to the MaxEnt distribution. MaxEnt-PCA (1) is rotation invariant, (2) is free from any distribution assumption, and (3) is robust to outliers. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed linear method as compared to other related robust PCA methods.

Changes:

Initial Announcement on mloss.org.


Logo ClowdFlows 0.9

by janezkranjc - October 8, 2013, 02:57:49 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4789 views, 879 downloads, 1 subscription

About: ClowdFlows is a web based platform for service oriented data mining publicly available at http://clowdflows.org . A web based interface allows users to construct data mining workflows that are hosted on the web and can be (if allowed by the author) accessed by anyone by following a URL of the workflow.

Changes:

Initial Announcement on mloss.org.


Logo The Choquet Kernel 1.00

by AliFall - February 11, 2014, 16:21:15 CET [ BibTeX BibTeX for corresponding Paper Download ] 2652 views, 878 downloads, 1 subscription

About: The package computes the optimal parameters for the Choquet kernel

Changes:

Initial Announcement on mloss.org.


Logo Nilearn 0.1.2

by goulagman - April 29, 2015, 16:16:25 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3804 views, 877 downloads, 3 subscriptions

About: Nilearn is a Python module for fast and easy statistical learning on NeuroImaging data. It leverages the scikit-learn Python toolbox for multivariate statistics with applications such as predictive modelling, classification, decoding, or connectivity analysis.

Changes:

Initial Announcement on mloss.org.


Logo MROGH 1.0

by openpr_nlpr - October 16, 2012, 04:41:51 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4345 views, 875 downloads, 1 subscription

About: An implementation of MROGH descriptor. For more information, please refer to: “Bin Fan, Fuchao Wu and Zhanyi Hu, Aggregating Gradient Distributions into Intensity Orders: A Novel Local Image Descriptor, CVPR 2011, pp.2377-2384.” The most up-to-date information can be found at : http://vision.ia.ac.cn/Students/bfan/index.htm

Changes:

Initial Announcement on mloss.org.


Logo MLFlex 02-21-2012-00-12

by srp33 - April 3, 2012, 16:44:43 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4318 views, 874 downloads, 1 subscription

About: Motivated by a need to classify high-dimensional, heterogeneous data from the bioinformatics domain, we developed ML-Flex, a machine-learning toolbox that enables users to perform two-class and multi-class classification analyses in a systematic yet flexible manner. ML-Flex was written in Java but is capable of interfacing with third-party packages written in other programming languages. It can handle multiple input-data formats and supports a variety of customizations. MLFlex provides implementations of various validation strategies, which can be executed in parallel across multiple computing cores, processors, and nodes. Additionally, ML-Flex supports aggregating evidence across multiple algorithms and data sets via ensemble learning. (See http://jmlr.csail.mit.edu/papers/volume13/piccolo12a/piccolo12a.pdf.)

Changes:

Initial Announcement on mloss.org.


Showing Items 481-490 of 642 on page 49 of 65: First Previous 44 45 46 47 48 49 50 51 52 53 54 Next Last