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CHANGELOG.md

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Changelog

v0.4.1 (2026-01-20)

  • Add Scholar.FeatureExtraction.CountVectorizer
  • Add Scholar.NaiveBayes.Categorical
  • Add Scholar.Optimize.Brent
  • Add Scholar.Optimize.GoldenSection
  • Improve Scholar.Cluster.DBSCAN's performance
  • General fixes to Scholar.Linear.LinearRegression

v0.4.0 (2025-01-15)

  • Require Nx ~> 0.9
  • Add batching to regression metrics
  • Add Scholar.Cluster.OPTICS
  • Add Scholar.Covariance.LedoitWolf
  • Add Scholar.Covariance.ShrunkCovariance
  • Add Scholar.CrossDecomposition.PLSSVD
  • Add Scholar.Decomposition.TruncatedSVD
  • Add Scholar.Impute.KNNImputter
  • Add Scholar.NaiveBayes.Bernoulli
  • Add Scholar.Preprocessing.Binarizer
  • Add Scholar.Preprocessing.RobustScaler
  • Add partial_fit/2 and incremental_fit/2 to PCA
  • Split RNN into Scholar.Neighbors.RadiusNNClassifier and Scholar.Neighbors.RadiusNNRegressor
  • Unify shape checks across all APIs

v0.3.1 (2024-06-18)

Enhancements

  • Add a notebook about manifold learning
  • Make knn algorithm configurable on Trimap
  • Add d2_pinball_score and d2_absolute_error_score

v0.3.0 (2024-05-29)

Enhancements

  • Add LargeVis for visualization of large-scale and high-dimensional data in a low-dimensional (typically 2D or 3D) space
  • Add Scholar.Neighbors.KDTree and Scholar.Neighbors.RandomProjectionForest
  • Add Scholar.Metrics.Neighbors
  • Add Scholar.Linear.BayesianRidgeRegression
  • Add Scholar.Cluster.Hierarchical
  • Add Scholar.Manifold.Trimap
  • Add Mean Pinball Loss function
  • Add Matthews Correlation Coefficient function
  • Add D2 Tweedie Score function
  • Add Mean Tweedie Deviance function
  • Add Discounted Cumulative Gain function
  • Add Precision Recall f-score function
  • Add f-beta score function
  • Add convergence check to AffinityPropagation
  • Default Affinity Propagation preference to reduce_min and make it customizable
  • Move preprocessing functionality to their own modules with fit and fit_transform callbacks

Breaking changes

  • Split KNearestNeighbors into KNNClassifier and KNNRegressor with custom algorithm support

v0.2.1 (2023-08-30)

Enhancements

  • Remove VegaLite.Data in favour of future use of Tucan
  • Do not use EXLA at compile time in Metrics

v0.2.0 (2023-08-29)

This version requires Elixir v1.14+.

Enhancements

  • Update notebooks
  • Add support for :f16 and :bf16 types in SVD
  • Add Affinity Propagation
  • Add t-SNE
  • Add Polynomial Regression
  • Replace seeds with Random.key
  • Add 'unrolling loops' option
  • Add support for custom optimizers in Logistic Regression
  • Add Trapezoidal Integration
  • Add AUC-ROC, AUC, and ROC Curve
  • Add Simpson rule integration
  • Unify tests
  • Add Radius Nearest Neighbors
  • Add DBSCAN
  • Add classification metrics: Average Precision Score, Balanced Accuracy Score, Cohen Kappa Score, Brier Score Loss, Zero-One Loss, Top-k Accuracy Score
  • Add regression metrics: R2 Score, MSLE, MAPE, Maximum Residual Error
  • Add support for axes in Confusion Matrix
  • Add support for broadcasting in Metrics.Distances
  • Update CI
  • Add Gaussian Mixtures
  • Add Model selection functionalities: K-fold, K-fold Cross Validation, Grid Search
  • Change structure of metrics in Scholar
  • Add a guide with Cross-Validation and Grid Search

v0.1.0 (2023-03-29)

First release.