topic Re: Alternatives for xg boost in Machine Learning

Alternatives for xg boost

Dk_1802 — Thu, 29 Jun 2023 22:51:24 GMT

Are there any alternatives for xg boost that work well with pyspark?

Re: Alternatives for xg boost

spark_ds — Thu, 29 Jun 2023 23:02:40 GMT

XGboost is now an option in pyspark pipelines (link here) but PysparkML also supports a number of alternatives including

Gradient-Boosted Trees (GBTs): Gradient-boosted trees is another boosting ensemble technique that learns from its mistakes in previous iterations. For this one can use the GBTClassifier from pyspark.ml.classification.
Random Forest: Random Forest is a bagging ensemble learning method. For this one can use the RandomForestClassifier from pyspark.ml.classification.
Decision Tree Classifier: The decision tree is a simple yet effective machine learning algorithm. For this one can use theDecisionTreeClassifier from pyspark.ml.classification.

Re: Alternatives for xg boost

Vinay_M_R — Fri, 30 Jun 2023 10:32:25 GMT

Spark MLlib GBT: Spark MLlib, the machine learning library included with Apache Spark, provides its own implementation of gradient boosting trees (GBT). It offers similar functionality to XGBoost and can be used directly within PySpark ML pipelines without requiring external libraries.