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It's also important to apply feature scaling if regularization is used as part of the loss function (so that coefficients are penalized appropriately). Empirically, feature scaling can improve the convergence speed of stochastic gradient descent. In support vector machines, [2] it can reduce the time to find support vectors. Feature scaling is ...
Using a database-specific stored procedure that generates the surrogate key, performs the INSERT operation, and finally returns the generated key. For example, in Microsoft SQL Server, the key is retrieved via the SCOPE_IDENTITY() special function, while in SQLite the function is named last_insert_rowid().