JuliaAI / JuliaAI/MLJTestInterface.jl
Add data set for text analysis
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- Dominant language
- Julia
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- 0
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- 2
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- Merged PRs (30d)
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Description
Taken from the MLJText.jl requirements for transformers:
Generate a vector whose elements are either tokenized documents or bags of words/ngrams. Specifically, each element would be one of the following:
-
A vector of abstract strings (tokens), e.g., ["I", "like", "Sam",
".", "Sam", "is", "nice", "."] (scitype AbstractVector{Textual}) -
A dictionary of counts, indexed on abstract strings, e.g.,
Dict("I"=>1, "Sam"=>2, "Sam is"=>1) (scitype Multiset{Textual}}) -
A dictionary of counts, indexed on plain ngrams, e.g.,
Dict(("I",)=>1, ("Sam",)=>2, ("I", "Sam")=>1) (scitype
Multiset{<:NTuple{N,Textual} where N}); here a plain ngram is a
tuple of abstract strings.
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
No file, test, or entry point is named; start by reading the repository structure and the referenced MLJText.jl transformer requirements. Done means adding a data set representing tokenized documents, word or ngram count dictionaries, and plain ngram count dictionaries as described in the issue.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100