You are viewing the RapidMiner Radoop documentation for version 9.0 - Check here for latest version
What's new in RapidMiner Radoop 9.0
This page describes the new features of RapidMiner Radoop 9.0 as well as its enhancements and bug fixes. Note that RapidMiner Radoop 9.0 is backwards compatible and requires at least RapidMiner Studio 8.1 and RapidMiner Server 8.1 or higher. Update is available through RapidMiner Marketplace.
Anomaly detection
Find the needle in the haystack. Identify fraud, detect abnormal consumer or machine behavior or spot rare but interesting facts by detecting outliers in your data on Hadoop with the new Anomaly Detection operator implementing the Isolation Forest algorithm.
Windowing
Solve time series use cases like forecasting, predictive maintenance and others directly in Hadoop. Use the new windowing operator to easily restructure your time series data residing in Hadoop in a way that can be understood by prediction, clustering and outlier detection algorithms.
Discretization
Reduce overfitting of machine learning models and improve their predictive performance by preparing data with the new discretization operators in RapidMiner Radoop. Binning or bucketing techniques are useful whenever the exact number representing a value is not meaningful and only adds noise and they are a great tool to prepare data for algorithms such as decision trees.
Support for MapR 6
Easily analyze data and use all the predictive power of RapidMiner Radoop in a MapR 6 Hadoop environment.
Enhancements and bug fixes
The following pages describe the enhancements and bug fixes in RapidMiner Radoop 9.0 releases: