## Bias & Variance in laymen Terms

If the machine learning model is not generalised then the model contains some kind of error.Error= difference between actual and predicted values/classesFormulae = sum of (actual output-predicted output), Also Error is the sum of reducible + irreducible error. Reducible Error= bias + varianceBias is how far is the predicted values/class from actual values/class. If the predicted value is too far… Continue reading "Bias & Variance in laymen Terms"