Workload Characterization Techniques

• Terminology
• Components and Parameter Selection
• Workload Characterization Techniques
• Averaging
• Case Study: Program Usage in Educational Environments
• Characteristics of an Average Editing Session
• Single Parameter Histograms
• Multi-parameter Histograms
• Principal Component Analysis
• Finding Principal Factors
• Principal Component Example
• Principal Component Example
• Markov Models
• Transition Probability
• Clustering
• Clustering Steps
• 1. Sampling
• 2. Parameter Selection
• 3. Transformation
• 4. Outliers
• 5. Data Scaling
• Distance Metric
• Clustering Techniques
• Minimum Spanning Tree-Clustering Method
• Minimum Spanning Tree Example
• Dendogram
• Nearest Centroid Method
• Cluster Interpretation
• Problems with Clustering
• Summary
• Exercise 6.1

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