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About: Debellor is a scalable and extensible platform which provides common architecture for data mining and machine learning algorithms of various types. Changes:

About: Learns gradient boosted regression tree ensembles in parallel on shared memory or cluster systems Changes:Initial Announcement on mloss.org.

About: Classification and regression trees Changes:Fetched by rcranrobot on 20120201 00:00:11.999664

About: Regularization for semiparametric additive hazards regression Changes:Fetched by rcranrobot on 20161001 00:00:03.403247

About: This software implements the DeltaLDA model, which is a modification of the Latent Dirichlet Allocation (LDA) model. DeltaLDA can use multiple topic mixing weight priors to jointly model multiple [...] Changes:fixed some npy_intp[] memory leaks fixed phi normalization bug

About: A (randomized) coordinate descent procedure to minimize L1 regularized loss for classification and regression purposes. Changes:Fixed some I/O bugs. Lines that ended with whitespace were not read correctly in the previous version.

About: Heteroscedastic Discriminant Analysis Changes:Fetched by rcranrobot on 20130401 00:00:05.551691

About: A stochastic variant of the mirror descent algorithm employing Langford and Zhang's truncated gradient idea to minimize L1 regularized loss minimization problems for classification and regression. Changes:Fixed major bug in implementation. The components of the iterate where the current example vector is zero were not being updated correctly. Thanks to Jonathan Chang for pointing out the error to us.

About: BSVM solves support vector machines (SVM) for the solution of large classification and regression problems. It includes three methods Changes:Initial Announcement on mloss.org.

About: LibSGDQN proposes an implementation of SGDQN, a carefully designed quasiNewton stochastic gradient descent solver for linear SVMs. Changes:small bug fix (thx nicolas ;)
