What is the bias-variance tradeoff in Machine Learning?
- A tradeoff between supervised and unsupervised learning
- A tradeoff between the complexity and the size of a model
- A tradeoff between the learning rate and the number of epochs
- A tradeoff between underfitting and overfitting
The bias-variance tradeoff refers to the balancing act between underfitting (high bias, low variance) and overfitting (low bias, high variance). A model with high bias oversimplifies the problem, while high variance tends to overcomplicate it.
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