JuliaAI / JuliaAI/DecisionTree.jl
Does not handle Adjoint nor Transposed features
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- Dominant language
- Julia
- Stars
- 364
- Forks
- 100
- PR merge metrics
- No merged PRs in 30d
Description
in https://white.ucc.asn.au/2017/01/24/JuliaML-and-TensorFlow-Tuitorial.html
rows and columns are swapped, as columns are labeled samples instead of rows
ERROR: LoadError: MethodError: no method matching build_tree(::Array{Bool,1}, ::LinearAlgebra.Adjoint{Int64,Array{Int64,2}}, ...
using DecisionTree
import ScikitLearnBase: fit!
features = [1 2;4 5;3 6]
labels = [true,false]
println("As array");fit!(DecisionTreeClassifier(), convert(Array{Float64,2},features'), labels)
println("Adjoint");fit!(DecisionTreeClassifier(), features', labels)
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Reproduce the issue with the provided fit! examples, comparing the converted array with the Adjoint input and the build_tree MethodError. Start at the fit! entry point and the build_tree dispatch shown in the error; done means both Adjoint and Transposed feature inputs are accepted without this method error and retain the expected feature orientation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100