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Error Analysis & Insights #39

Description

@levelslip
  • Description: Deep dive analysis of model prediction errors
  • Activities:
    • Analyze systematic errors:
      • Identify consistent over/under-prediction patterns
      • Analyze error by time of day, department, etc
      • Quantify systematic bias
    • Identify error patterns:
      • Identify scenarios with high errors
      • Analyze error distributions
      • Identify error outliers
    • Propose improvement areas:
      • Suggest features that might help
      • Recommend data collection improvements
      • Recommend model architecture changes
    • Create error visualizations:
      • Residual plots
      • Error distributions by category
      • Prediction vs actual scatter plots
    • Document insights:
      • Write findings and recommendations
      • Create error analysis report
      • Suggest next steps for improvement
  • Deliverables: Error analysis report, recommendations for improvement

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