Utilizing Explainable AI Techniques

Apply explainability tools like SHAP or LIME to interpret model decisions and understand which features heavily influence retention predictions. Transparent explanations can uncover latent biases embedded within certain variables that correlate with sensitive attributes, prompting adjustments.

Apply explainability tools like SHAP or LIME to interpret model decisions and understand which features heavily influence retention predictions. Transparent explanations can uncover latent biases embedded within certain variables that correlate with sensitive attributes, prompting adjustments.

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Retention Forecasting Models for Diverse Tech Talent

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