# tGradientBoostedTreeModel

Analyzes feature vectors usually prepared and provided by tModelEncoder to generate a classifier model that is used by tPredict to classify given elements.

tGradientBoostedTreeModel analyzes incoming datasets using the Decision Tree algorithm.

It generates a binary classification model out of this analysis and writes this model either in memory or in a given file system.

In local mode, Apache Spark 1.6.0 and later versions are supported.

For more technologies supported by Talend, see [Talend components](https://help.qlik.com/talend/r/en-US/7.3/components/machine-learning).

### In this section

* [tGradientBoostedTreeModel properties for Apache Spark Batch](https://help.qlik.com/talend/en-US/components/7.3/machine-learning/tgradientboostedtreemodel-properties-for-apache-spark-batch)