The accuracy is simply how good your machine learning model is at predicting a correct class for a given observation. You build the model with training data and validate with the test data. What are the scenarios which have higher training accuracy and low test accuracy called?
The accuracy is simply how good your machine learning model is at predicting a correct class for a given observation. You build the model with training data and validate with the test data. What are the scenarios which have higher training accuracy and low test accuracy called?
a.Overfitting
b.High Bias
c.Low variance
d.Under fitting