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Bias(편향) : Gap between the real problem and our model / The expected error created by using a model to apporoximate a real world function/relationship. 모델을 통해 얻은 예측값과 실제 정답과의 차이의 평균 f hat(x) : predicted value f(x) : true value Bias[^f(x)]=E[^f(x)−f(x)] Variance(분산) : change for different training data sets / The amount our predicted values would change if we had a differenct training dataset. It..

Assessing Model Accuracy So many machine learning methods! • A single best method for all data sets? Nope! • One method may work best on a particular data set. • But, some other method may work better on a similar but different data set How to compare Methods? • Given a set of data, which method will produce the best result? • In other words, how to compare different learning methods? Measuring ..