SoftRandomForest v0.1.0

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Classification Random Forests for Soft Decision Trees

Performs random forests for soft decision trees for a classification problem. Current limitations are for a maximum depth of 5 resulting in 16 terminal nodes. Some data cleaning is required before input. Final graphic output requires currently requires exporting to 'Microsoft Excel' for visualization. Method based on Irsoy, Yildiz and Alpaydin (2012, ISBN: 978-4-9906441-1-6).

Functions in SoftRandomForest

Name Description
BestForestSplit Choosing the best variable for splitting.
SoftClassForest Implementing a Random Forest of SDTs.
SoftForestPredDepth1 Building a single level for the Random Forest of SDTs.
SoftClassMatrix Converting response vector to sparse matrix.
SoftForestPredFeeder Choosing the appropriate depth function.
SoftObservation Recording the prediction weights to analyze observation-level patterns
ClassMode Determining the mode from a vector of numbers.
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Details

Date 2019-05-05
License CC0
URL https://github.com/GregHilleren/SoftRandomForest
RoxygenNote 6.1.1
Encoding UTF-8
NeedsCompilation yes
Packaged 2019-05-13 14:25:03 UTC; Gregory
Repository CRAN
Date/Publication 2019-05-15 13:20:03 UTC
imports boot , utils
depends R (>= 3.4.0)
Contributors Gregory Hilleren

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