smartcore/CHANGELOG.md

Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[0.4.0] - 2023-04-05

Added

• WARNING: Breaking changes!
• DenseMatrix constructor now returns Result to avoid user instantiating inconsistent rows/cols count. Their return values need to be unwrapped with unwrap(), see tests

[0.3.0] - 2022-11-09

Added

• WARNING: Breaking changes!
• Complete refactoring with extensive API changes that includes:
  • moving to a new traits system, less structs more traits
  • adapting all the modules to the new traits system
  • moving to Rust 2021, use of object-safe traits and as_ref
  • reorganization of the code base, eliminate duplicates
• implements readers (needs "serde" feature) for read/write CSV file, extendible to other formats
• default feature is now Wasm-/Wasi-first

Changed

• WARNING: Breaking changes!
• Seeds to multiple algorithims that depend on random number generation
• Added a new parameter to train_test_split to define the seed
• changed use of "serde" feature

Dropped

• WARNING: Breaking changes!
• Drop nalgebra-bindings feature, only ndarray as supported library

[0.2.1] - 2021-05-10

Added

• L2 regularization penalty to the Logistic Regression
• Getters for the naive bayes structs
• One hot encoder
• Make moons data generator
• Support for WASM.

Changed

• Make serde optional

[0.2.0] - 2021-01-03

Added

• DBSCAN
• Epsilon-SVR, SVC
• Ridge, Lasso, ElasticNet
• Bernoulli, Gaussian, Categorical and Multinomial Naive Bayes
• K-fold Cross Validation
• Singular value decomposition
• New api module
• Integration with Clippy
• Cholesky decomposition

Changed

• ndarray upgraded to 0.14
• smartcore::error:FailedError is now non-exhaustive
• K-Means
• PCA
• Random Forest
• Linear and Logistic Regression
• KNN
• Decision Tree

[0.1.0] - 2020-09-25

Added

• First release of smartcore.
• KNN + distance metrics (Euclidian, Minkowski, Manhattan, Hamming, Mahalanobis)
• Linear Regression (OLS)
• Logistic Regression
• Random Forest Classifier
• Decision Tree Classifier
• PCA
• K-Means
• Integrated with ndarray
• Abstract linear algebra methods
• RandomForest Regressor
• Decision Tree Regressor
• Serde integration
• Integrated with nalgebra
• LU, QR, SVD, EVD
• Evaluation Metrics