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Hands-On Machine Learning with C# by Matt R. Cole

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Amount of training data

As we have said repeatedly, there simply is no substitute for having enough data to get the job done correctly and completely. This directly correlates to the complexity of your learning algorithm. A less complex algorithm with high bias and low variance can learn better from a smaller amount of data. However, if your learning algorithm is complex (many input features, parameters, and so on), then you will need a much larger training set from which to learn from with low bias and high variance.

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