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Logo hapFabia 1.4.2

by hochreit - December 28, 2013, 17:24:29 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 6652 views, 1287 downloads, 1 subscription

About: hapFabia is an R package for identification of very short segments of identity by descent (IBD) characterized by rare variants in large sequencing data. It detects 100 times smaller segments than previous methods.

Changes:

o citation update

o plot function improved


Logo Harry 0.4.2

by konrad - April 16, 2016, 10:50:38 CET [ Project Homepage BibTeX Download ] 11435 views, 2471 downloads, 3 subscriptions

About: A Tool for Measuring String Similarity

Changes:

This release fixes the incorrect implementation of the bag distance.


Logo hca 0.63

by wbuntine - April 26, 2016, 15:35:03 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ] 26459 views, 3502 downloads, 4 subscriptions

About: Multi-core non-parametric and bursty topic models (HDP-LDA, DCMLDA, and other variants of LDA) implemented in C using efficient Gibbs sampling, with hyperparameter sampling and other flexible controls.

Changes:

Corrected the new normalised Gamma model for topics so it works with multicore. Improvements to documentation. Added an asymptotic version of the generalised Stirling numbers so it longer fails when they run out of bounds on bigger data.


Logo hcluster 0.2.0

by damianeads - December 14, 2008, 14:03:49 CET [ Project Homepage BibTeX Download ] 4033 views, 1055 downloads, 1 subscription

About: This library provides Python functions for agglomerative clustering. Its features include

Changes:

Initial Announcement on mloss.org.


Logo HDDM 0.5

by Wiecki - April 24, 2013, 02:53:07 CET [ Project Homepage BibTeX Download ] 6784 views, 1645 downloads, 1 subscription

About: HDDM is a python toolbox for hierarchical Bayesian parameter estimation of the Drift Diffusion Model (via PyMC). Drift Diffusion Models are used widely in psychology and cognitive neuroscience to study decision making.

Changes:
  • New and improved HDDM model with the following changes:
    • Priors: by default model will use informative priors (see http://ski.clps.brown.edu/hddm_docs/methods.html#hierarchical-drift-diffusion-models-used-in-hddm) If you want uninformative priors, set informative=False.
    • Sampling: This model uses slice sampling which leads to faster convergence while being slower to generate an individual sample. In our experiments, burnin of 20 is often good enough.
    • Inter-trial variablity parameters are only estimated at the group level, not for individual subjects.
    • The old model has been renamed to HDDMTransformed.
    • HDDMRegression and HDDMStimCoding are also using this model.
  • HDDMRegression takes patsy model specification strings. See http://ski.clps.brown.edu/hddm_docs/howto.html#estimate-a-regression-model and http://ski.clps.brown.edu/hddm_docs/tutorial_regression_stimcoding.html#chap-tutorial-hddm-regression
  • Improved online documentation at http://ski.clps.brown.edu/hddm_docs
  • A new HDDM demo at http://ski.clps.brown.edu/hddm_docs/demo.html
  • Ratcliff's quantile optimization method for single subjects and groups using the .optimize() method
  • Maximum likelihood optimization.
  • Many bugfixes and better test coverage.
  • hddm_fit.py command line utility is depracated.

Logo Hidden Markov Support Vector Machines 0.2

by pramod - April 16, 2010, 17:27:41 CET [ BibTeX Download ] 7565 views, 1850 downloads, 1 subscription

About: This software is an implementation of Hidden Markov Support Vector Machines (HMSVMs).

Changes:

Initial Announcement on mloss.org.


About: Hierarchical Recurrent Neural Network for Skeleton Based Action Recognition

Changes:

Initial Announcement on mloss.org.


Logo HierLearning 1.0

by neville - March 2, 2014, 04:24:37 CET [ BibTeX BibTeX for corresponding Paper Download ] 2819 views, 771 downloads, 1 subscription

About: HierLearning is a C++11 implementation of a general-purpose, multi-agent, hierarchical reinforcement learning system for sequential decision problems.

Changes:

Initial Announcement on mloss.org.


About: The High-Dimensional Data Clustering (HDDC) toolbox contains an efficient unsupervised classifier for high-dimensional data. This classifier is based on a mixture of Gaussian models adapted for [...]

Changes:

Initial Announcement on mloss.org.


About: The High Dimensional Discriminant Analysis (HDDA) toolbox contains an efficient supervised classifier for high-dimensional data. This classifier is based on Gaussian models adapted for [...]

Changes:

Initial Announcement on mloss.org.


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