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    Unlocking the Potential: Machine Learning Driven Explainable AI Applications Across Diverse Domains

    Abstract: Explainable artificial intelligence (XAI) aims to make discoveries and output generated by machine learning algorithms accessible to human users in a trustworthy and easy-to-understand manner. It describes the impact of an AI model and any potential biases, helping in characterizing models with accuracy, fairness, transparency, and outcomes in decision-making powered by AI. XAI focuses on understanding the data used to train the model, its predictions, the specific elements involved in …

    Published in International Journal of Software Computing and Testing · Vol. 9, Issue 1, 2023 · pp. 24–32 Read article

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