Model Overfitting, Underfitting, Generalization and Cross Validation Simple Explanation and Examples
In this video, we describe Overfitting, Underfitting, Generalization and Cross Validation.
Generalize model is good to apply this for unseen data. Overfitted model gives good results on training but gives poor results on Test data.
Underfitting is concept when a model gives poor results on training results as well and we are not sure about its impact on test data.
Generalization is the concepts when a model gives reasonably good results on training and test data.
cross validation is the concepts of randomization of training and test data so that the model has the impact of all data on training and test data.
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Model Overfitting, Underfitting, Generalization and Cross Validation Simple Explanation and Examples
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