Subkey

Default

Options

fastr

True

True, False

fastr_plugin

LinearExecution

Any fastr execution plugin .

classifiers

SVM, RF, LR, LDA, QDA, GaussianNB, AdaBoostClassifier, XGBClassifier

SVM , SVR, SGD, SGDR, RF, LDA, QDA, ComplementND, GaussianNB, AdaBoostClassifier, XGBClassifier, LR, RFR, Lasso, ElasticNet, LinR, Ridge, AdaBoostRegressor, XGBRegressor. All are estimators from sklearn

max_iter

100000

Integer

SVMKernel

linear, poly, rbf

poly, linear, rbf

SVMC

0, 6

Two Integers: loc and scale

SVMdegree

1, 6

Two Integers: loc and scale

SVMcoef0

0, 1

Two Integers: loc and scale

SVMgamma

-5, 5

Two Integers: loc and scale

RFn_estimators

10, 90

Two Integers: loc and scale

RFmin_samples_split

2, 3

Two Integers: loc and scale

RFmax_depth

5, 5

Two Integers: loc and scale

LRpenalty

l1, l2, elasticnet

none, l2, l1

LRC

0.01, 0.99

Two Floats: loc and scale

LR_solver

lbfgs, saga

Comma separated list of strings, for the options see https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html

LR_l1_ratio

0, 1

Float between 0.0 and 1.0.

LDA_solver

svd, lsqr, eigen

svd, lsqr, eigen

LDA_shrinkage

-5, 5

Two Integers: loc and scale

QDA_reg_param

-5, 5

Two Integers: loc and scale

ElasticNet_alpha

-5, 5

Two Integers: loc and scale

ElasticNet_l1_ratio

0, 1

Two Integers: loc and scale

SGD_alpha

-5, 5

Two Integers: loc and scale

SGD_l1_ratio

0, 1

Two Integers: loc and scale

SGD_loss

squared_loss, huber, epsilon_insensitive, squared_epsilon_insensitive

hinge, squared_hinge, modified_huber

SGD_penalty

none, l2, l1

none, l2, l1

CNB_alpha

0, 1

Two Integers: loc and scale

AdaBoost_n_estimators

10, 90

Two Integers: loc and scale

AdaBoost_learning_rate

0.01, 0.99

Two Floats: loc and scale

XGB_boosting_rounds

10, 90

Two Integers: loc and scale

XGB_max_depth

3, 12

Two Integers: loc and scale

XGB_learning_rate

0.01, 0.99

Two Floats: loc and scale

XGB_gamma

0.01, 9.99

Two Floats: loc and scale

XGB_min_child_weight

1, 6

Two Integers: loc and scale

XGB_colsample_bytree

0.3, 0.7

Two Floats: loc and scale

LightGBM_num_leaves

5, 95

Two Integers: loc and scale

LightGBM_max_depth

3, 12

Two Integers: loc and scale

LightGBM_min_child_samples

5, 45

Two Integers: loc and scale

LightGBM_reg_alpha

0.01, 0.99

Two Floats: loc and scale

LightGBM_reg_lambda

0.01, 0.99

Two Floats: loc and scale

LightGBM_min_child_weight

-7, 4

Two Integers: loc and scale