risk minimizationの例文

例文

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1. Typical learning algorithms include empirical risk minimization, without or with Tikhonov regularization.
2. Empirical risk minimization seeks the function that best fits the training data.
3. This approach is called " empirical risk minimization, " or ERM.
4. Structural risk minimization seeks to prevent overfitting by incorporating a regularization penalty into the optimization.
5. When \ lambda = 0, this gives empirical risk minimization with low bias and high variance.