SHAP vs LightGBM
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description Overview
SHAP
SHAP, short for SHapley Additive exPlanations, is an open-source framework and library for interpreting machine learning predictions. It draws on Shapley values from game theory to assign contributions to input features. These values help explain how a model's output relates to a chosen baseline, making individual predictions easier to inspect than a result shown on its own.
Visualizations can al...
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LightGBM
Developed by Microsoft, LightGBM is a gradient boosting framework that builds ensembles of decision trees. Its histogram-based approach groups feature values into bins, helping reduce the work and memory needed during training. Leaf-wise tree growth expands the leaf offering the greatest improvement rather than growing every level uniformly, which can make learning efficient but also requires care...
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