cabal-version: 2.4 name: dataframe-learn version: 1.0.2.0 synopsis: Decision trees and feature synthesis for the dataframe ecosystem. description: @DataFrame.DecisionTree@ — decision-tree training on DataFrames. @DataFrame.Synthesis@ — feature synthesis. Built on top of @dataframe-operations@. bug-reports: https://github.com/mchav/dataframe/issues license: MIT license-file: LICENSE author: Michael Chavinda maintainer: mschavinda@gmail.com copyright: (c) 2024-2026 Michael Chavinda category: Data tested-with: GHC ==9.4.8 || ==9.6.7 || ==9.8.4 || ==9.10.3 || ==9.12.2 common warnings ghc-options: -Wincomplete-patterns -Wincomplete-uni-patterns -Wunused-imports -Wunused-local-binds -Wunused-packages library import: warnings exposed-modules: DataFrame.DecisionTree DataFrame.DecisionTree.Types DataFrame.DecisionTree.CondVec DataFrame.DecisionTree.Cart DataFrame.DecisionTree.Numeric DataFrame.DecisionTree.Prune DataFrame.DecisionTree.Predict DataFrame.DecisionTree.Categorical DataFrame.DecisionTree.Pool DataFrame.DecisionTree.Linear DataFrame.DecisionTree.Tao DataFrame.DecisionTree.Fit DataFrame.LinearSolver DataFrame.Synthesis build-depends: base >= 4 && < 5, containers >= 0.6.7 && < 0.9, parallel ^>= 3.2, dataframe-core ^>= 1.0, dataframe-operations ^>= 1.1, text >= 2.0 && < 3, vector ^>= 0.13, vector-algorithms ^>= 0.9 hs-source-dirs: src default-language: Haskell2010