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Machine learning algorithms, Machine learning models performance evaluation functionality
Last release 2 months ago
26 Jul 2026
Release timing varies
gaps range from 2 weeks to 13 months
Nearly every release is documented
notes for 60 of the last 60 stable releases
Nothing withdrawn
no release was ever pulled
8 years old
170 releases · first in 2018
- Remove obsolete contacts
Added MetricType.logLoss and LogLossMetric for evaluating probabilistic binary classifiers
MetricType.logLoss and LogLossMetric for evaluating probabilistic
binary classifiersAdded Decision Tree web demo using Web Assembly
One column per quarter.
fix the getIrisDataFrame and Pipeline example
- Update contacts in README
- Upgrade injector dependency
Gradient descent example corrected
dart 3.0 migration (non-breaking changes)
- ml_linalg ^13.11.15 used
ml_linalg version fixed (13.11.11)
- ml_linalg 13.11.1 used
Added links to articles to README
Removed package:ml_linalg/linalg.dart and package:ml_algo/ml_algo.dart imports
dtype passeddtype passedpackage:ml_linalg/linalg.dart and package:ml_algo/ml_algo.dart importsPedantic dependency removed in favour of dart lints package
more stable tests for LinearRegressor
- LogisticRegressor: - Newton method added
- LinearRegressor: - Newton method added
LinearRegressor, LogisticRegressor, SoftmaxRegressor:
fitIntercept param to true by defaultREADME: LogisticRegressor example corrected
LinearRegressor.BGD constructor added
LinearRegressor.BGD constructor addedLinearRegressor.SGD constructor added
LinearRegressor.SGD constructor addedRandomBinaryProjectionSearcher:
RandomBinaryProjectionSearcher:
ml_algo export file:
kd_tree export file:
Corrected link to RandomBinaryProjectionSearcher class in README.md
RandomBinaryProjectionSearcher class in README.mdRandomBinaryProjectionSearcher class added
RandomBinaryProjectionSearcher class addedgetPimaIndiansDiabetesDataFrame, getIrisDataFrame used
getPimaIndiansDiabetesDataFrame, getIrisDataFrame usedToy datasets from ml_dataframe package used
ml_dataframe package usedfromIterable constructor, default value for splitting strategy changed
KDTree:
fromIterable constructor, default value for splitting strategy changedREADME:
kd_tree exported as a separate library
KDTree example added to READMEkd_tree exported as a separate libraryml_preprocessing version upgraded to 7.0.2
ml_preprocessing version upgraded to 7.0.2ml_dataframe version upgraded to 1.0.0- KnnClassifier: - Proofreading the documentation
- DecisionTreeClassifier: - Proofreading the documentation
- CrossValidator: - Proofreading the documentation
- KDTree: - Corrected usage example
- README.md: - Proofreading the texts
- KDTree: - Added queryIterable method
queryIterable methodSupported cosine, manhattan and hamming distance
cosine, manhattan and hamming distance- DecisionTreeClassifier: - Added Gini index assessor type
Added example of DecisionTreeClassifier usage to README.md
README.mdFixed greedy splitter in case of a split column consisting of the same values
Added saveAsSvg method which returns '.svg' file with a graphical representation of a tree
saveAsSvg method which returns '.svg' file with a graphical representation of a treesplitStrategy option added to all constructors
fromIterable constructor addedsplitStrategy option added to all constructorsKDTree build optimization: split algorithm changed
KDTree class added to library export file
KDTree class added to library export file- Added KDTree algorithm
KDTree algorithmAdd ecosystem notes to README.md
README.mdAdded linear regression examples to README.md
README.mdAdded LinearRegressor.SGD constructor
LinearRegressor.SGD constructorAdded LinearRegressor.lasso constructor
LinearRegressor.lasso constructorCoordinated descent optimizer speed up
README: Added example of linear regression
README: Added example of linear regressionAdded closed-form solution for linear regression
Corrected typos and mistakes in README and documentation
e2e tests: linear regressor's config improved
Linear optimization-based algorithms: default parameters organised and extracted to separate files
Documentation for learning rate strategies added
stepBased learning rate strategy added
stepBased learning rate strategy addedtimeBased and exponential learning rate strategies added
timeBased and exponential learning rate strategies added- README: learning rate examples
README: learning rate examplesdartfmt applied to the project files
dartfmt applied to the project filesRetrainable: returning type was fixed
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