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Stability is a model's capacity to remain accurate even when small changes are made to its training data or construction. Think of it like building a tower with blocks; if it is constructed poorly, even minor winds could bring it down; on the other hand, if built robustly and securely, even strong winds won't knock it over. We can make our tower stronger using techniques like cross-validation, bootstrapping, and regularization. | Stability is a model's capacity to remain accurate even when small changes are made to its training data or construction. Think of it like building a tower with blocks; if it is constructed poorly, even minor winds could bring it down; on the other hand, if built robustly and securely, even strong winds won't knock it over. We can make our tower stronger using techniques like cross-validation, bootstrapping, and regularization. | ||
[[Category:Terms]] [[Category:Machine learning terms]] | [[Category:Terms]] [[Category:Machine learning terms]] [[Category:not updated]] |