Explainable Machine Learning For Dynamic Pricing In Fast-Changing Retail Environments

Key Points

• Dynamic pricing models enhanced by explainable machine learning techniques can adapt rapidly to market fluctuations.
• Model accuracy increased by 15% when using explainable algorithms compared to standard approaches.
• Assessment using a large dataset from multiple retail sectors showed promising applications in pricing strategies.
• Highlights the need for explainable AI in retail to build trust and enhance decision-making processes.