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#Org.apache.spark.mllib.optimization Classes and Interfaces - 11 results found.
NameDescriptionTypePackageFramework
Gradient Class used to compute the gradient for a loss function, given a single data point.Classorg.apache.spark.mllib.optimizationApache Spark
GradientDescentClass used to solve an optimization problem using Gradient Descent.Classorg.apache.spark.mllib.optimizationApache Spark
HingeGradient Compute gradient and loss for a Hinge loss function, as used in SVM binary classification.Classorg.apache.spark.mllib.optimizationApache Spark
L1Updater Updater for L1 regularized problems.Classorg.apache.spark.mllib.optimizationApache Spark
LBFGS Class used to solve an optimization problem using Limited-memory BFGS.Classorg.apache.spark.mllib.optimizationApache Spark
LeastSquaresGradient Compute gradient and loss for a Least-squared loss function, as used in linear regression.Classorg.apache.spark.mllib.optimizationApache 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).Classorg.apache.spark.mllib.optimizationApache Spark
Optimizer Trait for optimization problem solvers.Interfaceorg.apache.spark.mllib.optimizationApache Spark
SimpleUpdater A simple updater for gradient descent *without* any regularization.Classorg.apache.spark.mllib.optimizationApache Spark
SquaredL2Updater Updater for L2 regularized problems.Classorg.apache.spark.mllib.optimizationApache Spark
Updater Class used to perform steps (weight update) using Gradient Descent methods.Classorg.apache.spark.mllib.optimizationApache Spark