How does bias and variance relate with the training/testing error in Machine Learning. In layman terms does high variance means high testing error

Question

How does bias and variance relate with the training/testing error in Machine Learning. In layman terms does high variance means high testing error

honolulu

2022年2月24日 05:10

What causes high BIAS/VARIANCE and what are the consequences. Can some one explain in simple terms w.r.t to training/testing errors . Thanks

Topic variance linear-regression reinforcement-learning classification machine-learning

Category Data Science

Ashwiniku918 · Accepted Answer · 2022年2月24日 05:10

It Bias and Variance Tradeoff which most ML models try to optimise.

Bias : High Bias classifier learned on the training set is not expressive enough to even account for the data provided. In this case, both the training error and the test error will be high, as the classifier does not account for relevant information present in the training set.

Variance : The classifier learned on the training set is too specific, and cannot be used to accurately infer anything about unseen data. Although training error continues to decrease over time, test error will begin to increase again as the classifier begins to make decisions based on patterns which exist only in the training set and not in the broader distribution.

Please refer to image below for more details :

How does bias and variance relate with the training/testing error in Machine Learning. In layman terms does high variance means high testing error

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