Question

in machine learning if sample training data is too less what happen​

Answer 1

Answer:

Generally, it is common knowledge that too little training data results in a poor approximation. An over-constrained model will underfit the small training dataset, whereas an under-constrained model, in turn, will likely overfit the training data, both resulting in poor performance.

Explanation:

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