The Anomaly Detection Extension comprises the most well know unsupervised anomaly detection algorithms, assigning individual anomaly scores to data rows of example sets

This extension provides Deep Learning capabilities for execution on CPU and GPU.

This RapidMiner-plugin consists of operators for feature selection and classification - mainly on high-dimensional (microarray-) data - and some helper-classes/operators.

This extension provides two new operators, Foreacast (Univariate) and Forecast (Multivariate) which allow simple but powerful forecasting of time series.

This extension provides two new operators, Foreacast (Univariate) and Forecast (Multivariate) which allow simple but powerful forecasting of time series.

This extension offers two operators to access OpenAI's APIs for generating text and images.

The Generative Models extension (aka Generative AI) offers access to large language models (LLM) from Huggingface and OpenAI as well as finetuning of those models. It also offers embedding operators and vector stores and therefore support Retrieval-Augmented Generation (RAG).

This extension includes a set of operators for information selection form the training set for classification and regression problems. These are operators for instance selection (example set selection), instance construction (creation of new examples that represent a set of other instances), clustering, LVQ neural networks, dimensionality reduction, and other. These operators can be used for outlier elimination and training set compression.

This extension gives you additional operators from the space of interpretation and explainable AI. At the moment it covers LIME, SHAP and Shapely. Note that this is an alpha version.

The Keras extension allows to use Keras, a high-level Python library for Deep Learning leveraging Tensorflow, Microsoft Cognitive Toolkit (CNTK) or Theano as computation backends.

MonkeyLearn is an AI platform that allows companies to easily analyze text with Machine Learning. Customers like Clearbit, Segment and Drift are using MonkeyLearn to turn emails, support tickets, customer feedback, and documents into actionable data.

A collection of useful operators that add extra functionality to RapidMiner.

This extension offers an operator to do prescriptive optimization. This means you vary the values of an example to optimize a custom fitness function which may derive from a model. Currently supported optimizers: - Grid - Evolutionary - BYOBA

The Sales Forecasting model developed by Cappius uses a user defined window to predict future value of a time series by using Linear regression. The model that could be used are Neural networks or SVMs. The model performance is also evaluated by performing Residual analysis.

This extension wraps functionality from the Smile library (http://haifengl.github.io/smile/) and provides them as operators.

Word2Vec is a popular algorithm based on: Efficient Estimation of Word Representations in Vector Space, Mikolov et. al (2013). Training on a single corpus the algorithm will generate one multidimensional vector for each word. These vectors are known to have symantic meanings. A commonly used distance measure is cosine similarity. This implementation is based on the word2vec port available at: https://github.com/allenai/Word2VecJava

This extension embeds the XGBoost eXtreme Gradient Boosting library for use in RapidMiner. It implements a single operator named XGBoost compatible with RapidMiner's builtin learners.