# tRandomForestModel

Analyzes feature vectors.

These vectors are usually pre-processed by tModelEncoder to generate a classifier model that is used by tPredict to classify given elements.

tRandomForestModel analyzes incoming datasets based on applying the Random Forest algorithm.

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

In local mode, Apache Spark 1.3, 1.4, 1.5, 1.6, 2.0, 2.3, 2.4 and 3.0 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

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

**Related concepts**

[Creating a classification model to filter spam](https://help.qlik.com/talend/en-US/components/7.3/machine-learning/classification-model)