20 projects found that use the bsd license.
Showing Items 1-20 of 82 on page 1 of 5: 1 2 3 4 5 Next

Logo Databases for DMNS source codes 1.0

by openpr_nlpr - May 15, 2018, 07:56:12 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 213 views, 38 downloads, 2 subscriptions

About: In DMNS source, five databases are used in slover.cpp and data_veh_layer.cpp, these images and databases are included in this file, except munich database.

Changes:

Initial Announcement on mloss.org.


Logo Source codes of DMNS based on caffe platform 1.0

by openpr_nlpr - May 15, 2018, 07:52:48 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 205 views, 39 downloads, 2 subscriptions

About: Deep measuring net sequence(DMNS) is a sequence of three deep measuring nets, the later are deep fcn-based networks, directely output object category score, object orientation, location and scale simultaneously without any anchor boxes. DMNS acheived high accuracy in maneuvering target detection and geometrical measurements. Its average orientation error is less than 3.5 degree, loaction error less than 1.3 pixel, scale measuring error less than 10%, achieve a detection F1-score 96.5% in OAD, 91.8% in SVDS ,90.8% in Munich , 87.3% in OIRDS, outperforms SSD, Fater R-CNN, etc.

Changes:

Initial Announcement on mloss.org.


Logo JMLR MLPACK 3.0.1

by rcurtin - May 11, 2018, 05:28:53 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 107727 views, 19352 downloads, 6 subscriptions

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About: A fast, flexible C++ machine learning library, with bindings to other languages.

Changes:

Released May 10th, 2018.

  • Fix intermittently failing tests (#1387).
  • Add Big-Batch SGD (BBSGD) optimizer in src/mlpack/core/optimizers/bigbatch_sgd (#1131).
  • Fix simple compiler warnings (#1380, #1373).
  • Simplify NeighborSearch constructor and Train() overloads (#1378).
  • Add warning for OpenMP setting differences (#1358/#1382). When mlpack is compiled with OpenMP but another application linking against mlpack is not (or vice versa), a compilation warning will now be issued.
  • Restructured loss functions in src/mlpack/methods/ann/ (#1365).
  • Add environments for reinforcement learning tests (#1368, #1370, #1329).
  • Allow single outputs for multiple timestep inputs for recurrent neural networks (#1348).
  • Neural networks: add He and LeCun normal initializations (#1342), add FReLU and SELU activation functions (#1346, #1341), add alpha-dropout (#1349).

Logo rupture, change point detection in Python 1.0

by truongx - January 3, 2018, 09:51:55 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 1561 views, 415 downloads, 2 subscriptions

About: ruptures is a Python library for off-line change point detection. This package provides methods for the analysis and segmentation of non-stationary signals. Implemented algorithms include exact and approximate detection for various parametric and non-parametric models. ruptures focuses on ease of use by providing a well-documented and consistent interface. In addition, thanks to its modular structure, different algorithms and models can be connected and extended within this package.

Changes:

Initial Announcement on mloss.org.


Logo HIERDENC 1.0

by billandreo - October 31, 2017, 16:01:32 CET [ Project Homepage BibTeX Download ] 2793 views, 2523 downloads, 2 subscriptions

About: This is a tool for retrieving nearest neighbors and clustering of large categorical data sets represented in transactional form. The clustering is achieved via a locality-sensitive hashing of categorical datasets for speed and scalability.

Changes:

Initial Announcement on mloss.org.


Logo Calibrated AdaMEC 1.0

by nnikolaou - April 8, 2017, 13:57:45 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 2868 views, 551 downloads, 3 subscriptions

About: Code for Calibrated AdaMEC for binary cost-sensitive classification. The method is just AdaBoost that properly calibrates its probability estimates and uses a cost-sensitive (i.e. risk-minimizing) decision threshold to classify new data.

Changes:

Updated license information


Logo scikit multilearn 0.0.5

by niedakh - February 25, 2017, 03:51:59 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5503 views, 1201 downloads, 3 subscriptions

About: A native Python, scikit-compatible, implementation of a variety of multi-label classification algorithms.

Changes:
  • a general matrix-based label space clusterer has been added which can cluster the output space using any scikit-learn compatible clusterer (incl. k-means)
  • support for more single-class and multi-class classifiers you can now use problem transformation approaches with your favourite neural networks/deep learning libraries: theano, tensorflow, keras, scikit-neuralnetworks
  • support for label powerset based stratified kfold added
  • graph-tool clusterer supports weighted graphs again and includes stochastic blockmodel calibration
  • bugs were fixed in: classifier chains and hierarchical neuro fuzzy clasifiers

Logo FEAST 2.0.0

by apocock - January 8, 2017, 00:49:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 54514 views, 9285 downloads, 4 subscriptions

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About: FEAST provides implementations of common mutual information based filter feature selection algorithms (mim, mifs, mrmr, cmim, icap, jmi, disr, fcbf, etc), and an implementation of RELIEF. Written for C/C++ & Matlab.

Changes:

Major refactoring of FEAST to improve speed and portability.

  • FEAST now clones the input data if it's floating point and discretises it to unsigned ints once in a single pass. This improves the speed by about 30%.
  • FEAST now has unsigned int entry points which avoid this discretisation and are much faster if the data is already categorical.
  • Added weighted feature selection algorithms to FEAST which can be used for cost-sensitive feature selection.
  • Added a Java API using JNI.
  • FEAST now returns the internal score for each feature according to the criterion. Available in all three APIs.
  • Rearranged the repository to make it easier to work with. Header files are now in `include`, source in `src`, the MATLAB API is in `matlab/` and the Java API is in `java/`.
  • FEAST now compiles cleanly using `-std=c89 -Wall -Werror`.

Logo QMiner 5.0.0

by blazfortuna - April 8, 2016, 14:17:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 5885 views, 1097 downloads, 2 subscriptions

About: Analytic engine for real-time large-scale streams containing structured and unstructured data.

Changes:

Initial Announcement on mloss.org.


Logo Cognitive Foundry 3.4.2

by Baz - October 30, 2015, 06:53:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 40146 views, 6807 downloads, 4 subscriptions

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

Changes:
  • General:
    • Upgraded MTJ to 1.0.3.
  • Common:
    • Added package for hash function computation including Eva, FNV-1a, MD5, Murmur2, Prime, SHA1, SHA2
    • Added callback-based forEach implementations to Vector and InfiniteVector, which can be faster for iterating through some vector types.
    • Optimized DenseVector by removing a layer of indirection.
    • Added method to compute set of percentiles in UnivariateStatisticsUtil and fixed issue with percentile interpolation.
    • Added utility class for enumerating combinations.
    • Adjusted ScalarMap implementation hierarchy.
    • Added method for copying a map to VectorFactory and moved createVectorCapacity up from SparseVectorFactory.
    • Added method for creating square identity matrix to MatrixFactory.
    • Added Random implementation that uses a cached set of values.
  • Learning:
    • Implemented feature hashing.
    • Added factory for random forests.
    • Implemented uniform distribution over integer values.
    • Added Chi-squared similarity.
    • Added KL divergence.
    • Added general conditional probability distribution.
    • Added interfaces for Regression, UnivariateRegression, and MultivariateRegression.
    • Fixed null pointer exception that can happen in K-means with an empty cluster.
    • Fixed name of maxClusters property on AgglomerativeClusterer (was called maxMinDistance).
  • Text:
    • Improvements to LDA Gibbs sampler.

Logo Optunity 1.1.1

by claesenm - September 30, 2015, 07:06:17 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 12835 views, 2659 downloads, 3 subscriptions

About: Optunity is a library containing various optimizers for hyperparameter tuning. Hyperparameter tuning is a recurrent problem in many machine learning tasks, both supervised and unsupervised.This package provides several distinct approaches to solve such problems including some helpful facilities such as cross-validation and a plethora of score functions.

Changes:

This minor release has the same feature set as Optunity 1.1.0, but incorporates several bug fixes, mostly related to the specification of structured search spaces.


Logo JMLR Darwin 1.9

by sgould - September 8, 2015, 06:50:37 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 78702 views, 16002 downloads, 4 subscriptions

About: A platform-independent C++ framework for machine learning, graphical models, and computer vision research and development.

Changes:

Version 1.9:

  • Replaced drwnInPaint class with drwnImageInPainter class and added inPaint application
  • Added function to read CIFAR-10 and CIFAR-100 style datasets (see http://www.cs.utoronto.ca/~kriz/cifar.html)
  • Added drwnMaskedPatchMatch, drwnBasicPatchMatch, drwnSelfPatchMatch and basicPatchMatch application
  • drwnPatchMatchGraph now allows multiple matches to the same image
  • Upgraded wxWidgets to 3.0.2 (problems on Mac OS X)
  • Switched Mac OS X compilation to libc++ instead of libstdc++
  • Added Python scripts for running experiments and regression tests
  • Refactored drwnGrabCutInstance class to support both GMM and colour histogram model
  • Added cacheSortIndex to drwnDecisionTree for trading-off speed versus memory usage
  • Added mexLoadPatchMatchGraph for loading drwnPatchMatchGraph objects into Matlab
  • Improved documentation, other bug fixes and performance improvements

Logo LMW Tree 1.0

by cdevries - May 30, 2015, 11:42:23 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3845 views, 811 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

Changes:

Initial Announcement on mloss.org.


Logo ClusterEval 1.1

by cdevries - May 18, 2015, 22:01:01 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 8291 views, 1780 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'.

Changes:

Moved project to GitHub.


Logo BLOG 0.9.1

by jxwuyi - April 27, 2015, 06:52:05 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 4432 views, 960 downloads, 3 subscriptions

About: Bayesian Logic (BLOG) is a probabilistic modeling language. It is designed for representing relations and uncertainties among real world objects.

Changes:

Initial Announcement on mloss.org.


Logo java machine learning platform 1.0

by openpr_nlpr - April 2, 2015, 09:02:14 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3949 views, 716 downloads, 2 subscriptions

About: Jmlp is a java platform for both of the machine learning experiments and application. I have tested it on the window platform. But it should be applicable in the linux platform due to the cross-platform of Java language. It contains the classical classification algorithm (Discrete AdaBoost.MH, Real AdaBoost.MH, SVM, KNN, MCE,MLP,NB) and feature reduction(KPCA,PCA,Whiten) etc.

Changes:

Initial Announcement on mloss.org.


Logo pyGPs 1.3.2

by mn - January 17, 2015, 13:08:43 CET [ Project Homepage BibTeX Download ] 13345 views, 2970 downloads, 4 subscriptions

About: pyGPs is a Python package for Gaussian process (GP) regression and classification for machine learning.

Changes:

Changelog pyGPs v1.3.2

December 15th 2014

  • pyGPs added to pip
  • mathematical definitions of kernel functions available in documentation
  • more error message added

Logo Lynx MATLAB Toolbox v0.8-beta

by ispamm - November 19, 2014, 00:56:07 CET [ Project Homepage BibTeX Download ] 3289 views, 803 downloads, 1 subscription

About: A MATLAB toolbox for defining complex machine learning comparisons

Changes:

Initial Announcement on mloss.org.


Logo BACOM2 1.0

by fydennis - October 24, 2014, 15:25:38 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 3776 views, 843 downloads, 2 subscriptions

About: revised version of BACOM

Changes:

Initial Announcement on mloss.org.


Logo RLPy 1.3a

by bobklein2 - August 28, 2014, 14:34:35 CET [ Project Homepage BibTeX Download ] 8308 views, 1740 downloads, 1 subscription

About: RLPy is a framework for performing reinforcement learning (RL) experiments in Python. RLPy provides a large library of agent and domain components, and a suite of tools to aid in experiments (parallelization, hyperparameter optimization, code profiling, and plotting).

Changes:
  • Fixed bug where results using same random seed were different with visualization turned on/off
  • Created RLPy package on pypi (Available at https://pypi.python.org/pypi/rlpy)
  • Switched from custom logger class to python default
  • Added unit tests
  • Code readability improvements (formatting, variable names/ordering)
  • Restructured TD Learning heirarchy
  • Updated tutorials

Showing Items 1-20 of 82 on page 1 of 5: 1 2 3 4 5 Next