Tag Archive for overfitting

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Bias and Variance

One of the key aspects of understanding prediction models is understanding the prediction error. It measures how good at predicting the model is and a simple way to compute is simply comparing the predicted values against the real observed counterparts (assuming a supervised learning scenario). But the job does not end with calculating the error because this might be large and hence it would… Read more →