MDS: supply Gram matrix directly
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- 难度
- 5/5
- 预计耗时
- 一周以上
- 新手友好度
- 30/100
- Issue 类型
- 功能
- 描述清晰度
- 基本清楚
- 活跃度
- 停滞
- 技术栈
- julia
调研方向
首先定位现有的 MDS 拟合入口,以及 issue 中提到的 dmat2gram 和 gram2dist 转换。在确定输入标记 API 之前,比较当前的坐标路径和距离路径;当支持直接输入 Gramian 且不破坏现有行为时,即表示完成。
由索引模型根据 Issue 内容生成。
描述
Currently the pipeline for MDS is X -> D -> G -> M, where X is a coordinate representation of the data, D is the pairwise distance matrix, G is the Gram matrix, and M is the final MDS model. One can alternatively go D -> G -> M by supplying the distances=true keyword. However, there are applications where the natural thing to supply is G. For example, if you are working with objects for which there is a natural inner product, and you want to visualize these objects in a lower-dimensional space, you're going to first compute G, and it would be quite silly to use fit(MDS, gram2dist(G); distances=true) when the first thing that will happen inside fit is to convert the distances back into the Gram matrix.
I know there isn't a ton of stuff inside fit that happens after you have G, but from the standpoint of keeping things in sync I think it would be best to expose this to the user instead of forcing them to create their own private version of fit.
The only hard problem is deciding the API. I think a good design would be
struct Distances{M<:AbstractMatrix}
D::M
end
struct Gramian{M<:AbstractMatrix}
G::M
end
fit(::Type{MDS}, X::AbstractMatrix) = fit(MDS, Distances(L2distance(X)))
fit(::Type{MDS}, D::Distances) = fit(MDS, Gramian(dmat2gram(D.D)))
function fit(::Type{MDS}, G::Gramian)
# the "main" implementation
end
Then users call one of:
fit(MDS, X)fit(MDS, Distances(D))fit(MSD, Gramian(G))
depending on what kind of starting point they have.
One alternative approach is to use a keyword argument, but here we would run into a compatibility problem: if we add gramian::Bool=false as a keyword, then we have to look for the case where distances == gramian == true and throw an error. This is not a big deal but it feels a bit ugly. Alternatively we could add interpretation=:coordinates and support the settings :distances and :gramian but that would be a breaking change. We can do a breaking change, but it seems to be a bit silly for a very minor change. With the "type tagging" of the input data, we could have fit(::Type{MDS}, X::AbstractMatrix) still support the distances kwarg but give a deprecation warning, and then we can remove that API whenever other more substantive changes force a breaking release.
- 主要语言
- Julia
- 星标
- 387
- 派生
- 83
- PR 合并指标
- 30 天内没有已合并 PR
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JuliaStats/MultivariateStats.jl 的其他 Issue
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难度 2/5 1-3 小时 新手友好度 72/100
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JuliaStats/MultivariateStats.jl#238 · 1 条评论 ·
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Return a result even when MetricMDS does not converge可能已有人在做 关联的 PR 仍在进行中或已合并。 未关闭
难度 4/5 3-5 天 新手友好度 35/100
JuliaStats/MultivariateStats.jl#233 · 1 条评论 ·
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难度 2/5 1-3 小时 新手友好度 35/100
JuliaStats/MultivariateStats.jl#231 · 2 条评论 ·
查看 JuliaStats/MultivariateStats.jl 的全部 Issue
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