MLDataUtils.jl
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JuliaML
Utility package for generating, loading, splitting, and processing Machine Learning datasets
This pull request changes the compat entry for the `LearnBase` package from `0.2, 0.3` to `0.2, 0.3, 0.6`. This keeps the compat entries for earlier versions. Note: I have not...
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It is often very useful to invert feature normalization. I think it would be a very nice addition to the `FeatureNormalizer` to add an `inverse` function that does exactly that.
I will comment on the rationale of the changes inline (as I might not understand all the details of the intended design).
This pull request changes the compat entry for the `LearnBase` package from `0.2, 0.3` to `0.2, 0.3, 0.5`. This keeps the compat entries for earlier versions. Note: I have not...
This pull request changes the compat entry for the `LearnBase` package from `0.2, 0.3` to `0.2, 0.3, 0.4`. This keeps the compat entries for earlier versions. Note: I have not...
To avoid training on imbalanced datasets, we usually sample data to a balance manner and ensure that every fold in cv contains all kinds of labels. I'd like to find...
So we can work with all types that implement the Tables.jl API. I think this will solve #39 as a side-effect, or at least will be solid progress towards that
Hi, Is there any function to create indices as in `kfolds()` but having them not overlapping and moving from first to last? I see two ways one would have it:...
Hi. I'm following the Getting Started tutorial and the following code for defining the Iris classifying model returns the error shown in the title. I'm new to Julia, and a...
Putting this here for visibility. See https://github.com/JuliaML/MLDataPattern.jl/pull/29 for fix.
