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Spark-ml-algo-lib-Spark2.4.6 v2.1.0
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@wyy566 wyy566 released this 30 Mar 02:48
· 2 commits to Spark2.4.6 since this release
v2.1.0-spark2.4.6
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Overview

In this version, the library provides 21 common learning algorithms based on Spark2.3,2: support vector machine (SVM), random forest (RF), gradient boosting decision tree (GBDT), k-means, decision tree, linear regression, logistic regression, principle component analysis (PCA), principal component analysis for Sparse Matrix(SPCA) 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, XGboost, Inverse Document Frequency(IDF), and SimRank. The library is optimized based on open-source Spark machine learning algorithms and provides required JAR files.

Changes

This release includes a patch and three new machine learning algorithms:
-feature: Added three 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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