Spark-ml-algo-lib-Spark3.1.1 v2.1.0

Overview

In this version, the library provides 5 machine learning algorithms: latent dirichlet allocation (LDA), prefix-projected pattern prowth (Prefix-Span), alternating least squares (ALS), K-nearest neighbors (KNN), Density-based spatial clustering of applicaitons with noise (DBSCAN).

Spark-ml-algo-lib-Spark2.4.6 v2.1.0

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.

Spark-ml-algo-lib-Spark2.3.2 v2.1.0

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 Spark2.3.2.

Spark-ml-algo-lib-spark2.4.6 v1.3.0

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.

Spark-ml-algo-lib-spark2.3.2 v1.3.0

Overview

In this version, the library provides 18 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) 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 Spark2.3.2.

Spark-ml-algo-lib v1.2.0

Overview

In this version, the library provides nine common learning algorithms: 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). The library is optimized based on open-source Spark machine learning algorithms and provides required JAR files.

Changes

This release includes a patch and four new machine learning algorithms:
-feature: Added four machine learning algorithms.
-patch: Released a patch based for the library.

v1.1.0

Overview

In this version, the library provides nine common learning algorithms: 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). The library is optimized based on open-source Spark machine learning algorithms and provides required JAR files.

Changes

This release includes a patch and six new machine learning algorithms:
-feature: Added six machine learning algorithms.
-patch: Released a patch based on the differences between the current and previous versions.

Spark-ml-algo-lib v1.0.0

Overview

In this version, the library provides three common learning algorithms: support vector machine (SVM), random forest classifier (RFC), and gradient boosting decision tree (GBDT). This library is optimized based on open-source Spark machine learning algorithms and provides required JAR files.

Changes

This release includes new machine learning algorithms, an introduction to the library, and a patch:
-feature: Added Spark machine learning algorithms.
-doc: Added an introduction to the library.
-patch: Released a patch for the library.