Skip to content

Commit

Permalink
Browse files Browse the repository at this point in the history
undo NEWS change that overwrote 2.0.0 NEWS item
  • Loading branch information
Soeren Sonnenburg committed Sep 5, 2012
1 parent 2a85752 commit 15ed292
Showing 1 changed file with 56 additions and 0 deletions.
56 changes: 56 additions & 0 deletions src/NEWS
Expand Up @@ -9,6 +9,62 @@
* Cleanup and API Changes:
- None

2012-09-01 Soeren Sonnenburg <sonne@debian.org>

* SHOGUN Release version 2.0.0 (libshogun 12.0, data 0.4, parameter 1)
* This release also contains several enhancements, cleanups and bugfixes:
* Features:
- This release contains first release of Efficient Dimensionality Reduction Toolkit (EDRT).
- Support for new SWIG -builtin python interface feature (SWIG 2.0.4 is required now).
- EDRT algorithms are now available using static interfaces such as matlab and octave.
- Jensen-Shannon kernel and Homogeneous kernel map preprocessor (thanks to Viktor Gal).
- New 'multiclass' module for multiclass classification algorithms, generic linear
and kernel multiclass machines, multiclass LibLinear and OCAS wrappers,
new rejection schemes concept by Sergey Lisitsyn.
- Various multitask learning algorithms including L1/Lq multitask group lasso logistic regression
and least squares regression, L1/L2 multitask tree guided group lasso logistic regression
and least squares regression, trace norm regularized multitask logistic regression, clustered multitask
logistic regression and L1/L2 multitask group logistic regression by Sergey Lisitsyn.
- Group and tree-guided logistic regression for binary and multiclass problems by Sergey Lisitsyn.
- Mahalanobis distance, QDA, Stochastic Proximity Embedding,
generic OvO multiclass machine and CoverTree & KNN integation (thanks to Fernando J. Iglesias Garcia).
- Structured output learning framework by Fernando J. Iglesias Garcia.
- Hidden markov support vector machine structured output model by Fernando J. Iglesias Garcia.
- Implementations of three Bundle method for risk minimization (BMRM) variants by Michal Uricar.
- Latent SVM framework and latent detector example by Viktor Gal.
- Gaussian processes framework for parameters selection and gaussian processes regression estimation
framework by Jacob Walker.
- New graphical python modular examples.
- Standard Cross-Validation splitting for regression problems by Heiko Strathmann
- New data-locking concept by Heiko Strathmann which allows to tell machines that data
is not going to change during training/testing until unlocked.
KernelMachines now make use of that by not recomputing kernel matrix in cross-validation.
- Cross-validation for KernelMachines is now parallelized.
- Cross-validation is now possible with custom kernels.
- Features may now have arbritarily many index subsets (of subsets (of subsets (...))).
- Various clustering measures, Least Angle Regression and new multiclass strategies
concept (thanks to Chiyuan Zhang).
- A bunch of multiclass learning algorithms including the ShareBoost algorithm, ECOC framework,
conditional probability tree, balanced conditional probability tree, random conditional probability
tree and relaxed tree by Chiyuan Zhang.
- Python Sparse matrix typemap for octave modular interface (thanks to Evgeniy Andreev).
- Newton SVM port (thanks to Harshit Syal).
- Some progress on native windows compilation using
cmake and mingw-w64 (thanks to Josh aka jklontz).
- CMake compilation improvements (thanks to Eric aka yoo).
* Bugfixes:
- Fix for bug in the Gaussian Naive Bayes classifier, its domain was
changed to log-space.
- Fix for R_static interface installation (thanks Steve Lianoglou).
- SVMOcas memsetting and max_train_time bugfix.
- Various fixes for compile errors with clang.
- Stratified-cross-validation now used different indices for each run.
* Cleanup and API Changes:
- Various code cleanups by Evan Shelhamer
- Parameter migration framework by Heiko Strathmann. From now on,
changes in the shogun objects will not break loading old serialized
files anymore

2011-12-01 Soeren Sonnenburg <sonne@debian.org>

* SHOGUN Release version 1.1.0 (libshogun 11.0, data 0.3, parameter 0)
Expand Down

0 comments on commit 15ed292

Please sign in to comment.