About:
The SHOGUN machine learning toolbox's focus is on large scale learning methods with focus on Support Vector Machines (SVM), providing interfaces to python, octave, matlab, r and the command line.
Changes:
This release features the work of our 8 GSoC 2014 students [student; mentors]:
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OpenCV Integration and Computer Vision Applications [Abhijeet Kislay; Kevin Hughes]
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Large-Scale Multi-Label Classification [Abinash Panda; Thoralf Klein]
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Large-scale structured prediction with approximate inference [Jiaolong Xu; Shell Hu]
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Essential Deep Learning Modules [Khaled Nasr; Sergey Lisitsyn, Theofanis Karaletsos]
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Fundamental Machine Learning: decision trees, kernel density estimation [Parijat Mazumdar ; Fernando Iglesias]
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Shogun Missionary & Shogun in Education [Saurabh Mahindre; Heiko Strathmann]
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Testing and Measuring Variable Interactions With Kernels [Soumyajit De; Dino Sejdinovic, Heiko Strathmann]
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Variational Learning for Gaussian Processes [Wu Lin; Heiko Strathmann, Emtiyaz Khan]
It also contains several cleanups and bugfixes:
Features
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New Shogun project description [Heiko Strathmann]
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ID3 algorithm for decision tree learning [Parijat Mazumdar]
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New modes for PCA matrix factorizations: SVD & EVD, in-place or reallocating [Parijat Mazumdar]
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Add Neural Networks with linear, logistic and softmax neurons [Khaled Nasr]
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Add kernel multiclass strategy examples in multiclass notebook [Saurabh Mahindre]
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Add decision trees notebook containing examples for ID3 algorithm [Parijat Mazumdar]
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Add sudoku recognizer ipython notebook [Alejandro Hernandez]
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Add in-place subsets on features, labels, and custom kernels [Heiko Strathmann]
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Add Principal Component Analysis notebook [Abhijeet Kislay]
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Add Multiple Kernel Learning notebook [Saurabh Mahindre]
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Add Multi-Label classes to enable Multi-Label classification [Thoralf Klein]
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Add rectified linear neurons, dropout and max-norm regularization to neural networks [Khaled Nasr]
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Add C4.5 algorithm for multiclass classification using decision trees [Parijat Mazumdar]
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Add support for arbitrary acyclic graph-structured neural networks [Khaled Nasr]
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Add CART algorithm for classification and regression using decision trees [Parijat Mazumdar]
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Add CHAID algorithm for multiclass classification and regression using decision trees [Parijat Mazumdar]
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Add Convolutional Neural Networks [Khaled Nasr]
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Add Random Forests algorithm for ensemble learning using CART [Parijat Mazumdar]
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Add Restricted Botlzmann Machines [Khaled Nasr]
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Add Stochastic Gradient Boosting algorithm for ensemble learning [Parijat Mazumdar]
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Add Deep contractive and denoising autoencoders [Khaled Nasr]
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Add Deep belief networks [Khaled Nasr]
Bugfixes
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Fix reference counting bugs in CList when reference counting is on [Heiko Strathmann, Thoralf Klein, lambday]
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Fix memory problem in PCA::apply_to_feature_matrix [Parijat Mazumdar]
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Fix crash in LeastAngleRegression for the case D greater than N [Parijat Mazumdar]
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Fix memory violations in bundle method solvers [Thoralf Klein]
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Fix fail in library_mldatahdf5.cpp example when http://mldata.org is not working properly [Parijat Mazumdar]
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Fix memory leaks in Vowpal Wabbit, LibSVMFile and KernelPCA [Thoralf Klein]
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Fix memory and control flow issues discovered by Coverity [Thoralf Klein]
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Fix R modular interface SWIG typemap (Requires SWIG >= 2.0.5) [Matt Huska]
Cleanup and API Changes
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PCA now depends on Eigen3 instead of LAPACK [Parijat Mazumdar]
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Removing redundant and fixing implicit imports [Thoralf Klein]
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Hide many methods from SWIG, reducing compile memory by 500MiB [Heiko Strathmann, Fernando Iglesias, Thoralf Klein]
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- Operating System:
Cygwin,
Linux,
Macosx,
Bsd
- Data Formats:
Plain Ascii,
Svmlight,
Binary,
Fasta,
Fastq,
Hdf
- JMLR-MLOSS Publication:
JMLR Page
- Tags:
Bioinformatics,
Large Scale,
String Kernel,
Kernel,
Kernelmachine,
Lda,
Lpm,
Matlab,
Mkl,
Octave,
Python,
R,
Svm,
Sgd,
Icml2010,
Liblinear,
Libsvm,
Multiple Kernel Learning,
Ocas,
Gaussian Processes,
Reg
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