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vruusmann committed Dec 29, 2023
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2 changes: 1 addition & 1 deletion .github/workflows/maven.yml
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on:
push:
branches: [ '2.0.X', '2.1.X', '2.2.X', '2.3.X', master ]
branches: [ '2.0.X', '2.1.X', '2.2.X', '2.3.X', '2.4.X', master ]

jobs:
build:
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11 changes: 9 additions & 2 deletions README.md
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Expand Up @@ -45,6 +45,8 @@ Java library and command-line application for converting Apache Spark ML pipelin
<details>
<summary>Apache Spark ML</summary>

Examples: [main.py](https://github.com/jpmml/jpmml-sparkml/blob/2.2.X/pmml-sparkml/src/test/resources/main.py)

* Feature extractors, transformers and selectors:
* [`feature.Binarizer`](https://spark.apache.org/docs/latest/api/java/org/apache/spark/ml/feature/Binarizer.html)
* [`feature.Bucketizer`](https://spark.apache.org/docs/latest/api/java/org/apache/spark/ml/feature/Bucketizer.html)
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<details>
<summary>LightGBM</summary>

Examples: [LightGBMAuditNA.scala](https://github.com/jpmml/jpmml-sparkml/blob/2.2.X/pmml-sparkml-lightgbm/src/test/resources/LightGBMAuditNA.scala), [LightGBMAutoNA.scaka](https://github.com/jpmml/jpmml-sparkml/blob/2.2.X/pmml-sparkml-lightgbm/src/test/resources/LightGBMAutoNA.scala), etc.

* Prediction models:
* [`com.microsoft.azure.synapse.ml.lightgbm.LightGBMClassificationModel`](https://mmlspark.blob.core.windows.net/docs/0.9.5/scala/com/microsoft/azure/synapse/ml/lightgbm/LightGBMClassificationModel.html)
* [`com.microsoft.azure.synapse.ml.lightgbm.LightGBMRegressionModel`](https://mmlspark.blob.core.windows.net/docs/0.9.5/scala/com/microsoft/azure/synapse/ml/lightgbm/LightGBMRegressionModel.html)
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<details>
<summary>XGBoost</summary>

Examples: [XGBoostAuditNA.scala](https://github.com/jpmml/jpmml-sparkml/blob/2.2.X/pmml-sparkml-xgboost/src/test/resources/XGBoostAuditNA.scala), [XGBoostAutoNA.scala](https://github.com/jpmml/jpmml-sparkml/blob/2.2.X/pmml-sparkml-xgboost/src/test/resources/XGBoostAutoNA.scala), etc.

* Prediction models:
* [`ml.dmlc.xgboost4j.scala.spark.XGBoostClassificationModel`](https://xgboost.readthedocs.io/en/latest/jvm/scaladocs/xgboost4j-spark/ml/dmlc/xgboost4j/scala/spark/XGBoostClassificationModel.html)
* [`ml.dmlc.xgboost4j.scala.spark.XGBoostRegressionModel`](https://xgboost.readthedocs.io/en/latest/jvm/scaladocs/xgboost4j-spark/ml/dmlc/xgboost4j/scala/spark/XGBoostRegressionModel.html)
</details>

# Prerequisites #

* Apache Spark 3.0.X, 3.1.X, 3.2.X, 3.3.X or 3.4.X.
* Apache Spark 3.0.X, 3.1.X, 3.2.X, 3.3.X, 3.4.X or 3.5.X.

# Installation #

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| 3.1.X | [`2.1.X`](https://github.com/jpmml/jpmml-sparkml/tree/2.1.X) |
| 3.2.X | [`2.2.X`](https://github.com/jpmml/jpmml-sparkml/tree/2.2.X) |
| 3.3.X | [`2.3.X`](https://github.com/jpmml/jpmml-sparkml/tree/2.3.X) |
| 3.4.X | [`master`](https://github.com/jpmml/jpmml-sparkml/tree/master) |
| 3.4.X | [`2.4.X`](https://github.com/jpmml/jpmml-sparkml/tree/2.4.X) |
| 3.5.X | [`master`](https://github.com/jpmml/jpmml-sparkml/tree/master) |

Archived development branches:

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