Overfitting and Underfitting in Machine Learning #artificialintelligence
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Overfitting and Underfitting in Machine Learning #artificialintelligence
In Machine Learning, the goal is to build models that learn patterns from training data and generalize well to unseen data. Two common pitfalls are overfitting and underfitting. Overfitting occurs when a model learns not only the true patterns but also the noise and outliers in the training data. This leads to low training error but high ...
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