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sylvaticus/BetaML.jl
[MLJ interface] NeuralNetworkClassifier falsely claims to support `Count` target

using BetaML using MLJBase X = (x1 = rand(5), x2 = rand(5)) y = [1, 2, 3, 2, 1] scitype(y) # AbstractVector{Count} M = BetaML.Bmlj.NeuralNetworkClassifier @assert scitype(y) : target_scitype(M) verbosity ...
  • ablaom
  • 2
  • Opened 
    on Dec 20, 2024
  • #75

sylvaticus/BetaML.jl
Scaling wish cache a matrix with non-numerical values result in an error

The problem is that both StandardScaler and MinMaxScaler _fit function start defining the outer container as X_scaled = cache ? float.(X) : nothing But if X has non-numerical values this result in an ...
  • sylvaticus
  • Opened 
    on Jul 16, 2024
  • #73

sylvaticus/BetaML.jl
Cosine distance

Is there not a typing error here? https://github.com/sylvaticus/BetaML.jl/blob/4bf2d55ad3d8cfddeebeaea8396f172c7448020b/src/Utils/Measures.jl#L15-L17 Cosine distance cosine_distance(x,y) = dot(x,y)/(norm(x)*norm(y)) ...
  • mlesnoff
  • 1
  • Opened 
    on Mar 15, 2024
  • #71

sylvaticus/BetaML.jl
MLJ Interface is not working anymore

The code modelType = @load RandomForestClassifier pkg = BetaML verbosity=1 mod = modelType( n_trees = 2, max_depth = 10 ) is not working in the latest version of BetaML.
  • rubsc
  • 6
  • Opened 
    on Feb 22, 2024
  • #70

sylvaticus/BetaML.jl
"`findall` is ambiguous" error

While working with BetaML, DataFrames and Chain, I found that importing BetaML leads to ambiguity in findall when working with the @chain macro. using Chain, DataFrames import BetaML as BML df = DataFrame(randn(100, ...
  • simonsteiger
  • 3
  • Opened 
    on Feb 9, 2024
  • #69

sylvaticus/BetaML.jl
Correct the predict in AutoEncoder to consider non-vector layer outputs

Change the loop order in cache/predict of the AutoEncoder to allow convolutional layers with non-array output in layers
  • sylvaticus
  • Opened 
    on Jan 30, 2024
  • #68

sylvaticus/BetaML.jl
Problem with MLJ interface for KMedoidsClusterer

import BetaML using MLJTestInterface @testset generic mlj interface test begin f, s = MLJTestInterface.test( [BetaML.Bmlj.KMeansClusterer,], MLJTestInterface.make_regression()[1]; ...
  • ablaom
  • 1
  • Opened 
    on Jan 28, 2024
  • #67

sylvaticus/BetaML.jl
BetaML v11.0 Gaussian Mixture Model not compatible with MLJ

I recently updated my packages and noticed that I couldn t create an MLJ machine with the Gaussian Mixture Model with BetaML v0.11.0. The older version v0.10.4 is working fine. I have not checked whether ...
  • CasBex
  • 7
  • Opened 
    on Jan 26, 2024
  • #66

sylvaticus/BetaML.jl
Bug in Clustering_MLJ caused by spelling mistake

Need fitesult - fitresult in https://github.com/sylvaticus/BetaML.jl/blob/df11d62af777dd3ea25c6df43910c8f725148bc4/src/Clustering/Clustering_MLJ.jl#L178 See also #64
  • ablaom
  • 3
  • Opened 
    on Jan 10, 2024
  • #65

sylvaticus/BetaML.jl
Bug in GMM caused by spelling mistake

Picked this up in an integration test: https://github.com/sylvaticus/BetaML.jl/blob/df11d62af777dd3ea25c6df43910c8f725148bc4/src/GMM/GMM_MLJ.jl#L325 fitesult should be fitresult
  • ablaom
  • 1
  • Opened 
    on Jan 9, 2024
  • #64
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