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Releases: neurodata/SPORF

Python v2.0.5

07 Aug 20:24
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New in Python v2.0.5

• Unsupervised Randomer Forest (URerF) has been added, see the new demo

CRAN v2.0.4

15 Mar 19:53
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Changes in 2.0.4:

  • Updated tests to accomodate the new sample() algorithm in R 3.5.3

Changes in 2.0.3:

  • The PrintTree function has been added to aid in viewing the
    cut-points, features, and other statistics in a particular tree of a
    forest.

  • Urerf now supports using the Bayesian information criterion (BIC) from
    the mclust package for determining the best split.

  • Feature importance calculations now correctly handle features whose
    weight vectors parametrize the same line. Also, when the projection
    weights are continuous we tabulate how many times a unique combination
    of features was used, ignoring the weights.

  • An issue where the split.cpp function split the data A into {A, {}}
    has been resolved by computing equivalence within some factor of
    machine precision instead of exactly.

CRAN v2.0.3

06 Feb 23:04
9873b68
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Changes in 2.0.3:

  • The PrintTree function has been added to aid in viewing the
    cut-points, features, and other statistics in a particular tree of a
    forest.

  • Urerf now supports using the Bayesian information criterion (BIC) from
    the mclust package for determining the best split.

  • Feature importance calculations now correctly handle features whose
    weight vectors parametrize the same line. Also, when the projection
    weights are continuous we tabulate how many times a unique combination
    of features was used, ignoring the weights.

  • An issue where the split.cpp function split the data A into {A, {}}
    has been resolved by computing equivalence within some factor of
    machine precision instead of exactly.

Version 2.0.2

04 Dec 16:30
ebaea9b
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Changes in 2.0.2:

  • The option rho in the RerF function has been re-named to sparsity to match with the algorithm explanation.

  • The default parameters sent to the RandMat* functions now properly account for categorical columns.

  • The defualts have changed for the following parameters:

    • min.parent = 1
    • max.depth = 0
    • stratify = TRUE
  • Predictions are made based on the average of posteriors rather than average of the predictions.

  • The included RandMat* functions have been re-structured for ease of use with their own examples and documentation. This should make it easier to create and include a user defined function to use as an input option.

  • We are now using testthat for all of our function tests moving forward.

  • Housekeeping: Updated the README and changed maintainers.

Published to CRAN

23 Aug 19:28
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v1.1.3

removed last dynamic memory call, modified .Rbuildignore to ignore th…