JuliaAI / JuliaAI/DecisionTree.jl

Support for DataFrame based data and model formulas

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Dominant language
Julia
Stars
364
Forks
100
PR merge metrics
No merged PRs in 30d

Description

Hello, thanks for writing this. I've benchmarked its use against the default randomForest implementation in R and have found it to be amazingly fast.

I was hoping to be able to use this library with DataFrames, including the Model Formula format api. I know that DataFrames currently doesn't support categorical data columns, but I think it is planned to be integrated.

I can try to help contribute to this, but it would be nice if this project was merged into the JuliaStats project first (I prefer to contribute to projects that are explicitly community owned).

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No implementation files or tests are identified. Start by reviewing the library's current public API and how Julia DataFrames and the Model Formula API are represented, then define the integration scope, including categorical columns. Done means the library accepts DataFrame-based data and model formulas with documented behavior and coverage.

Written by the indexing model from the issue text.

Assessment

Tech stack
julia
Domain
data, machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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