Boon Logic Application Interface Documentation

The Amber Streaming API provides a straight-forward interface to the Boon Nano clustering engine.

The Boon Nano: The Core Technology

Introduction to the Boon Nano

Examples of Patterns

Using the Boon Nano

Configuring the Boon Nano

Clustering Results

Nano Status: Accessing the Current Nano Model

Root Cause Analysis

Example

Amber: Streaming Analytics

Introduction to Amber

Operational Overview

• Amber Training Phases
• Amber Training Example

Definitions and Terminology

Configuring Amber

• Single-Feature Versus Multi-Feature Processing
• Single-Feature Processing
• Multi-Feature Processing (Sensor Fusion)
• Configuration Parameters

Amber Input Data Recommendations

• Confounding Features
• Redundant and Poorly Correlated Features
• Missing Data and Variable Sample Rates
• Categorical Data

Amber Training Recommendations

• The Autotuning Buffer
• The Training Buffer
• Anomalies During Training
• Using Pretraining
• Re-enabling Learning

Amber Outputs

• (ID) Cluster ID
• (SI) Smoothed Anomaly Index
• (RI) Raw Anomaly Index
• (AD) Anomaly Detections
• (AH) Anomaly History
• (AM) Anomaly Metric
• (AW) Amber Warning Level
• (RC) Root Cause Analysis

Amber Model Status

Examples

• Anomaly Detection in a Single-Sensor Asset
• Anomaly Detection in a Multi-Sensor Asset (Sensor Fusion)

Amber Licensing

Amber Programming Interfaces

• REST API
• Python SDK
• Javascript SDK
• C++ SDK
• Go SDK
• R SDK
• C# SDK

AVIS DICOM

Visual Inspection of Mammography Images