5.1.0

1. Release Smile Studio. Smile Studio is an interactive desktop application to help you be more productive in building and serving models with SMILE. Similar to Jupyter Notebooks, Smile Studio is a REPL (Read-Evaluate-Print-Loop) containing an ordered list of input/output cells. Cd into the bin directory of pre-built package in a terminal, type ./smile to enter Smile Studio. If you work in a headless environment without graphical interface, you may run ./smile shell to enter Smile Shell for Java, which pre-imports all major SMILE packages. If you prefer Scala, type ./smile scala to enter Smile Shell for Scala.
2. Rename package smile.base to smile.model.
3. Add smile.model.ClassificationModel and smile.model.RegressionModel for model persistence and serving with metadata.
4. Rename the method soft() and online() of class Classifier to isSoft() and isOnline().

5.0.2

1. Update smile-kotlin to Kotlin 2.3.0 for Java 25 support.
2. Remove SentencePiece class. See SentencePiece4J for a pure Java implementation.

5.0.1

1. Support Iceberg tables
2. Read Parquet files through Arrow
3. Assume UTC if no timezone info in data files
4. Add split and stratify methods to Bag class for training and testing data split
5. Remove Hadoop dependency
6. Pause publishing spark module as spark depends on hadoop, which runs only on java 8/11
7. Bug fixes

5.0.0

1. V5.x requires Java 25
2. Fully redesign linear algebra and tensor/matrix package
3. 20% faster on average

4.4.2

Bug fixes

4.4.1

Bug fixes

4.4.0

1. Swing plot API refactoring
2. Migrate to the Central Publisher Portal as OSSRH service will reach end-of-life.
3. Bug fixes

4.3.0

1. IterativeAlgorithmController to monitor training progress and early stop.
2. Refactor learning algorithm hyperparameters with record Options
3. Refactor partitioning clustering algorithms
4. Rename CLARANS to KMedoids
5. SpectralClustering for sparse feature count matrix with cosine similarity.
6. Move lambda function interface into smile.util.function package
7. Update scala code to Scala 3 syntax
8. block quote representation for LLM reasoning block
9. Add --host and --port options for inference endpoint
10. Add --line option to render inference output JSON objects in a line-by-line fashion
11. gradle build scripts

4.2.0

1. DataFrame is fully re-designed. See Data Processing for a tutorial of the new API.
2. Random Forest and Gradient Boosting are 30% faster.
3. LLM frontend supports MathML.
4. Add smile.datasets package including many open benchmark datasets and training formula.
5. Bug fixes.

4.1.0

1. Refactor Graph API
2. Add Prim's algorithm for MST
3. Add Held-Karp algorithm, Christofides algorithm, branch-and-bound TSP, 2-opt algorithm, and various heuristics algorithms for TSP
4. Add random projection tree and random projection forest
5. Add nearest neighbor descent algorithm
6. UMAP is 6X faster on large data
7. Refactor manifold algorithm APIs
8. Add Pairing Heap data structure
9. Bug fixes