This template detects anomalous data points in a dataset using an autoencoder algorithm. It features automated machine learning to facilitate use by business analysts and citizen data scientists. The Time Series release of the template includes time series analysis and clustering of anomalies
Analyze your Big Data FAST with the use of this accelerator. Gain insights into your historical data and act in real time on the current streams of data in conjunction with historical analysis to make crucial decisions when it matters.
Random Forest is an ensemble tree machine-learning algorithm. This template employs supervised learning to determine variable importance and make predictions. It features automated machine learning to facilitate use by business analysts and citizen data scientists.
Identify potentially fraudulent activities in a high-frequency transaction stream using TIBCO's Financial Fraud Detection Accelerator. Build supervised and unsupervised models and hot deploy these on the event processing platform. Score transactions in real-time and raise cases for investigation when potential fraud is detected.