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Spark-ml-algo-lib-spark2.4.6 v1.3.0
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@J493339298 J493339298 released this 08 Jul 07:00
· 4 commits to Spark2.4.6 since this release
v1.3.0-spark2.4.6
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Overview

In this version, the library provides 18 common learning algorithms based on Spark2.4,6: support vector machine (SVM), random forest (RF), gradient boosting decision tree (GBDT), k-means, decision tree, linear regression, logistic regression, principle component analysis (PCA) and singular value decomposition (SVD), Latent Dirichlet Allocation (LDA), Prefix-Projected Pattern Growth (PrefixSpan), Alternating Least Squares (ALS), K-Nearest Neighbors (KNN), Covariance, Density-based spatial clustering of applicaitons with noise (DBSCAN), Pearson, Spearman, and XGboost. The library is optimized based on open-source Spark machine learning algorithms and provides required JAR files.

Changes

This release includes a patch and five new machine learning algorithms:
-feature: Added five machine learning algorithms.
-patch: Released a patch based for the library.
-jar: Released 4 jars based on Centos7.6 and Spark2.4.6.

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