Scitree

Scitree is a collection of state-of-the-art algorithms for Decision Forest model algorithms.<br/> Basically this is a wrapper around the Yggdrasil Decision Forests C++ libraries. <br/>

precompiled files for architecture x only

Examples

dataset_train = # Dataset
dataset_predict = # Dataset

Scitree.Config.init()
|> Scitree.Config.label("class")
|> Scitree.Config.learner(:random_forest)
|> Scitree.Config.task(:classification)
|> Scitree.train(dataset_train)
|> Scitree.predict(dataset_predict)

more examples

Dependencies

• Python3 (Tested with version 3.8.10)
• NumPy installed for compiling Tensorflow
• Bazelisk (or Bazel 5.1.1)
• GCC >= 9.3.0
• build-essential (base-devel)

Getting started

In order to use Scitree, you will need Elixir installed. Then create an Elixir project via the mix build tool:

$ mix new my_app

Then you can add Scitree as dependency in your mix.exs. At the moment you will have to use a Git dependency while we work on our first release:

def deps do
  [
    {:scitree, "~> 0.1.0"}
  ]
end

Alternatively, inside a script or Livebook:

Mix.install([{:scitree, "~> 0.1.0"}])