Battle-tested XML and RMP blueprints ready to import into RapidMiner Studio or AI Hub, complete with parameterized sample data.
Each workflow ships with its .rmp file, sample data, and the full Studio pipeline.
Full-cycle anomaly segmentation for rotating factory turbines. Streams sensor logs through rolling time-series windows, synthesizes spectral features, fits a memory-tuned XGBoost model, and exports compiled binaries for edge scoring gateways.
Read Data → Windowing → AutoFeature-Gen → XGBoost → Performance → Edge Export
Brings transformer representations into RapidMiner without leaving the canvas. Streams tokenized sentence vectors into a regularized logistic regression with automated LDA topic clustering.
Customer Reviews → Text Cleaning → DeepNLP Embed → Logistic Regression → Topic Visualizer
Handles class imbalance with SMOTE and shifts the focus from accuracy to business risk: false negatives (a lost subscriber, $950) are weighted 9.5× over false positives (a retention discount, $100).
Telco Data → SMOTE Upsampling → Hyperparameter Tuning → Cost-Matrix Scoring → Slack Webhook
Sub-millisecond scoring configuration integrated directly into RapidMiner Studio simulation loops for latency benchmark auditing.
Credit Events → JaguarEdge Scorer → Latency Benchmark
Compatible with RapidMiner Studio 9.10 – 10.3.
In RapidMiner Studio choose File › Import Process…, or paste the XML straight onto the canvas with Ctrl+V.
Get any missing ones from the RapidMiner Marketplace, for example Text Processing or Python Scripting.
Point the Read CSV operator to the downloaded sample dataset and press Run.
Let's design the pipeline that answers it.
