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Upgrade to XGBoost 1.7.3 and serialize objective for XGBoostClassificationModel #847

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Merged
merged 4 commits into from
Feb 24, 2023
Merged

Upgrade to XGBoost 1.7.3 and serialize objective for XGBoostClassificationModel #847

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2213073
Serialize objective
harupy Feb 23, 2023
1f89f37
Add missing dot
harupy Feb 23, 2023
c5445c2
Try xgboost 1.7.3
harupy Feb 23, 2023
4102662
Update sparkLoad
harupy Feb 23, 2023
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5 changes: 4 additions & 1 deletion ...ark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/mleap/XGBoostClassificationModelOp.scala
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Expand Up @@ -40,7 +40,8 @@ class XGBoostClassificationModelOp extends SimpleSparkOp[XGBoostClassificationMo
withValue("missing", Value.float(obj.getOrDefault(obj.missing))).
withValue("infer_batch_size", Value.int(obj.getOrDefault(obj.inferBatchSize))).
withValue("use_external_memory", Value.boolean(obj.getOrDefault(obj.useExternalMemory))).
withValue("allow_non_zero_for_missing", Value.boolean(obj.getOrDefault(obj.allowNonZeroForMissing)))
withValue("allow_non_zero_for_missing", Value.boolean(obj.getOrDefault(obj.allowNonZeroForMissing))).
withValue("objective", Value.string(obj.getOrDefault(obj.objective)))
}

override def load(model: Model)
Expand All @@ -57,6 +58,7 @@ class XGBoostClassificationModelOp extends SimpleSparkOp[XGBoostClassificationMo
model.getValue("allow_non_zero_for_missing").map(o => xgb.setAllowNonZeroForMissing(o.getBoolean))
model.getValue("infer_batch_size").map(o => xgb.setInferBatchSize(o.getInt))
model.getValue("use_external_memory").map(o => xgb.set(xgb.useExternalMemory, o.getBoolean))
model.getValue("objective").map(o => xgb.set(xgb.objective, o.getString))
xgb
}
}
Expand All @@ -71,6 +73,7 @@ class XGBoostClassificationModelOp extends SimpleSparkOp[XGBoostClassificationMo
if(model.isSet(model.inferBatchSize)) xgb.setInferBatchSize(model.getOrDefault(model.inferBatchSize))
if(model.isSet(model.treeLimit)) xgb.setTreeLimit(model.getOrDefault(model.treeLimit))
if(model.isSet(model.useExternalMemory)) xgb.set(xgb.useExternalMemory, model.getOrDefault(model.useExternalMemory))
if(model.isSet(model.objective)) xgb.set(xgb.objective, model.getOrDefault(model.objective))
xgb
}

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2 changes: 1 addition & 1 deletion ...test/scala/ml/dmlc/xgboost4j/scala/spark/mleap/XGBoostClassificationModelParitySpec.scala
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Expand Up @@ -31,7 +31,7 @@ class XGBoostClassificationModelParitySpec extends SparkParityBase {
)

// These params are not needed for making predictions, so we don't serialize them
override val unserializedParams = Set("labelCol", "evalMetric", "objective")
override val unserializedParams = Set("labelCol", "evalMetric")

override val excludedColsForComparison = Array[String]("prediction")

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2 changes: 1 addition & 1 deletion project/Dependencies.scala
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Expand Up @@ -17,7 +17,7 @@ object Dependencies {
lazy val slf4jVersion = "1.7.36"
lazy val awsSdkVersion = "1.11.1033"
val tensorflowJavaVersion = "0.4.0" // Match Tensorflow 2.7.0 https://github.com/tensorflow/java/#tensorflow-version-support
val xgboostVersion = "1.6.1"
val xgboostVersion = "1.7.3"
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Let's see what happens with the latest version

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nice!

val breezeVersion = "1.2"
val hadoopVersion = "2.7.4" // matches spark version
val platforms = "windows-x86_64,linux-x86_64,macosx-x86_64"
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