Linear models

AdamClassifier([transformer, eta0, beta1, …])

Adam solver for linear classifier with random feature maps.

AdamRegressor([transformer, eta0, beta1, …])

Adam solver for linear regression with random feature maps.

AdaGradClassifier([transformer, eta0, loss, …])

AdaGrad solver for linear classifier with random feature maps.

AdaGradRegressor([transformer, eta0, loss, …])

AdaGrad solver for linear regression with random feature maps.

DoublySGDClassifier([transformer, eta0, …])

Doubly SGD solver for linear classifier with random feature maps.

DoublySGDRegressor([transformer, eta0, …])

Doubly SGD solver for linear regression with random feature maps.

SAGAClassifier([transformer, eta0, loss, C, …])

SAGA solver for linear classifier with random feature maps.

SAGARegressor([transformer, eta0, loss, C, …])

SAGA solver for linear regression with random feature maps.

SDCAClassifier([transformer, loss, C, …])

Stochastic dual coordinate ascent solver for linear classifier with random feature maps.

SDCARegressor([transformer, loss, C, alpha, …])

Stochastic dual coordinate ascent solver for linear regression with random feature maps.

SGDClassifier([transformer, eta0, loss, C, …])

SGD solver for linear classifier with random feature maps.

SGDRegressor([transformer, eta0, loss, C, …])

SGD solver for linear regression with random feature maps.

SparseMBClassifier([n_components, loss, …])

Linear classifier with feature map approximating the intersection (min) kernel by sparse explicit feature map, which was proposed by S.Maji and A.C.Berg.

SparseMBRegressor([n_components, loss, …])

Linear regression with feature map approximating the intersection (min) kernel by sparse explicit feature map, which was proposed by S.Maji and A.C.Berg.