Anomaly Detection using Random Forest

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Presentation transcript:

Lumada Analytics Example Machine Learning Solutions Anomaly Detection using Random Forest

Anomaly Detection using Random Forest Anomaly detection using fault assignment labeling Using Python stages Field mapping, expression stage, email notification, pipeline branching

Anomaly Detection using Random Forest Composition

Model Training Workflow Random Forest Training Workflow Batching Data Pipeline Python Training Model Training Data Models f(x) Data Lake (Solr) File Storage Service

Apply Model Workflow Cluster Assignment Workflow Streaming Data f(x) Pipeline CONNECTOR AMQP Python Apply Model AMQP Output Stage RabbitMQ Exchange f(x) E Results f(x) Expression Stage Events/Alerts Email Models File Storage Service