Python v2.0.5

New in Python v2.0.5

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

CRAN v2.0.4

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

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

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

v1.1.3

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