Comments (1)
Sorry. I think that the frequent pattern mining (item set mining) algorithms are outside the scope of Rumale. Rumale intends to support classification, regression, clustering, and dimensionality reduction (matrix decomposition) as with scikit-learn. It is recommended to implement that as a new gem.
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Related Issues (20)
- feature request: clustering metrics HOT 4
- fit_bias: false is the default parameter for LinearRegression. Too difficult to find out ? HOT 2
- Documentation HOT 4
- デフォルトのsolverを使った場合のRumale::LinearModel::LinearRegressionの結果が直感と合いません HOT 5
- Example 1. XOR data - fails HOT 2
- Unable to install gem under rvm on jruby-9.2.0.0 HOT 2
- Method similar to train_test_split of sklearn HOT 4
- Is there a way to show the classification report as in sklearn? HOT 6
- When loading dataset from libsvm file, determine size of line HOT 3
- stack level too deep HOT 13
- Online versions of algorithms HOT 3
- HDBSCAN HOT 1
- Feature request : UMAP HOT 3
- Cross validation: best score HOT 1
- teratail: Rubyにrumaleをインストールできません HOT 3
- Add option to store training summary HOT 1
- ラベル予測と機械学習の実行速度を上げたい HOT 1
- Required Ruby Version is unclear HOT 2
- Compatibility Inquiry: rumale 0.28.1 with Ruby 3.3.0 HOT 2
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