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ScalaNLP vs XGBoost: What are the differences?
Developers describe ScalaNLP as "A suite of machine learning and numerical computing libraries". ScalaNLP is a suite of machine learning and numerical computing libraries. On the other hand, XGBoost is detailed as "Scalable and Flexible Gradient Boosting". Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow.
ScalaNLP and XGBoost can be primarily classified as "Machine Learning" tools.
Some of the features offered by ScalaNLP are:
- ScalaNLP is the umbrella project for several libraries:
- Breeze is a set of libraries for machine learning and numerical computing
- Epic is a high-performance statistical parser and structured prediction library
On the other hand, XGBoost provides the following key features:
- Flexible
- Portable
- Multiple Languages
ScalaNLP is an open source tool with 2.94K GitHub stars and 674 GitHub forks. Here's a link to ScalaNLP's open source repository on GitHub.
