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#Org.apache.spark.mllib.optimization Classes and Interfaces - 11 results found.
| Name | Description | Type | Package | Framework |
| Gradient | Class used to compute the gradient for a loss function, given a single data point. | Class | org.apache.spark.mllib.optimization | Apache Spark |
| GradientDescent | Class used to solve an optimization problem using Gradient Descent. | Class | org.apache.spark.mllib.optimization | Apache Spark |
| HingeGradient | Compute gradient and loss for a Hinge loss function, as used in SVM binary classification. | Class | org.apache.spark.mllib.optimization | Apache Spark |
| L1Updater | Updater for L1 regularized problems. | Class | org.apache.spark.mllib.optimization | Apache Spark |
| LBFGS | Class used to solve an optimization problem using Limited-memory BFGS. | Class | org.apache.spark.mllib.optimization | Apache Spark |
| LeastSquaresGradient | Compute gradient and loss for a Least-squared loss function, as used in linear regression. | Class | org.apache.spark.mllib.optimization | Apache Spark |
| LogisticGradient | Compute gradient and loss for a multinomial logistic loss function, as used in multi-class classification (it is also used in binary logistic regression). | Class | org.apache.spark.mllib.optimization | Apache Spark |
| Optimizer | Trait for optimization problem solvers. | Interface | org.apache.spark.mllib.optimization | Apache Spark |
| SimpleUpdater | A simple updater for gradient descent *without* any regularization. | Class | org.apache.spark.mllib.optimization | Apache Spark |
| SquaredL2Updater | Updater for L2 regularized problems. | Class | org.apache.spark.mllib.optimization | Apache Spark |
| Updater | Class used to perform steps (weight update) using Gradient Descent methods. | Class | org.apache.spark.mllib.optimization | Apache Spark |