MLBase.jl
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JuliaStats
A set of functions to support the development of machine learning algorithms
This fix changes the interface to `confusmat` from ```julia confusmat(k::Integer, gts::IntegerVector, preds::IntegerVector) ``` to ```julia function confusmat(gts::IntegerVector, preds::IntegerVector) ``` here `k` is calculated automatically.
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Hi, I don't think roc function is working properly. Here's an example. `gt = [1,2,1,2,1,2,1,2,1,2]` `pr = [1,1,1,1,1,1,1,1,1,1]` `roc(gt, pr)` This produces p = 10 n = 0 tp =...
if the classes in `gt` or `pred` contains `0` the function `confusmat` errors out with the following error. ``` gr=[0,1,0,1] pr=[0,0,1,1] confusmat(2, gr, pr) ERROR: BoundsError: attempt to access 2×2...
This package on its own is not all that discoverable, plus a lot of the methodology is also relevant to "classical" statistics, not just to machine learning (e.g. cross validation,...
It can be implemented via `sample` family of functions from `StatsBase`. Example implementation with `sklearn`-like interface is [here](http://pastebin.com/gu6QQaqJ). If it's okay I can make a PR; what holds me from...
I am running `julia v0.4.5` under Mac OS X. `crossval.jl` example fails with the following error: ``` ERROR: LoadError: MethodError: `cross_validate` has no method matching cross_validate(::Function, ::Function, ::Int64, ::MLBase.Kfold, ::Base.Order.ReverseOrdering{Base.Order.ForwardOrdering})...
Is there any level of cooperation in `MLBase` with [`MachineLearning.jl`](https://github.com/benhamner/MachineLearning.jl/)? Perhaps a difference in scope?
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A set of functions to support the development of machine learning algorithms