Man pages for jeremyrcoyle/sl3
Pipelines for Machine Learning and Super Learning

args_to_listGet all args of parent call (both specified and defaults) as...
bsdsBicycle sharing time series dataset
call_with_argsCall with filtered argument list
cppSubset of growth data from the collaborative perinatal...
cpp_1yrSubset of growth data from the collaborative perinatal...
Custom_chainCustomize chaining for a learner
density_datSimulated data with continuous exposure
drop_offsets_chainChain while dropping offsetes
factors_to_indicatorsConvert Factors to indicators
keep_only_fun_argsStreamline Function Arguments
learner_helpersLearner helpers
list_learnersList sl3 Learners
loss_functionsLoss Function Definitions
Lrnr_arimaUnivariate ARIMA Models
Lrnr_bartMachineBART Machine Learner
Lrnr_baseBase Class for all sl3 Learners.
Lrnr_bilstmBidirectional Long short-term memory Recurrent Neural Network...
Lrnr_condensierConditional Density Estimation
Lrnr_cvFit/Predict a learner with Cross Validation
Lrnr_dbartsDiscrete Bayesian Additive Regression Tree sampler
Lrnr_define_interactionsDefine interactions terms
Lrnr_expSmoothExponential Smoothing
Lrnr_glmGeneralized Linear Models
Lrnr_glm_fastComputationally Efficient GLMs
Lrnr_glmnetGLMs with Elastic Net Regularization
Lrnr_grfGeneralized Random Forests Learner
Lrnr_h2o_glmh2o Model Definition
Lrnr_h2o_gridGrid Search Models with h2o
Lrnr_hal9001The Scalable Highly Adaptive LASSO
Lrnr_HarmonicRegHarmonic Regression
Lrnr_independent_binomialClassification from Binomial Regression
Lrnr_lstmLong short-term memory Recurrent Neural Network (LSTM)
Lrnr_meanFitting Intercept Models
Lrnr_nnlsNon-negative Linear Least Squares
Lrnr_optimOptimize Metalearner according to Loss Function using optim
Lrnr_pcaPrincipal Component Analysis and Regression
Lrnr_pkg_condensier_logisfitR6sl3 Learner wrapper for condensier
Lrnr_randomForestRandom Forests
Lrnr_rangerRanger - A Fast Implementation of Random Forests
Lrnr_rpartLearner for Recursive Partitioning and Regression Trees.
Lrnr_rugarchUnivariate GARCH Models
Lrnr_slSuperLearner Algorithm
Lrnr_solnpNonlinear Optimization via Augmented Lagrange
Lrnr_solnp_densityNonlinear Optimization via Augmented Lagrange
Lrnr_subset_covariatesLearner with Covariate Subsetting
Lrnr_svmSupport Vector Machines
Lrnr_tsDynNonlinear Time Series Analysis
Lrnr_xgboostxgboost: eXtreme Gradient Boosting
make_learner_stackMake a stack of sl3 learners
metalearnersCombine predictions from multiple learners
pack_predictionsPack multidimensional predictions into a vector (and unpack...
PipelinePipeline (chain) of learners.
predict_classesPredict Class from Predicted Probabilities
prediction_plotPlot predicted and true values for diganostic purposes
replace_add_user_argsReplace an argument in 'mainArgs' if it also appears in...
riskRisk Esimation
safe_dimdim that works for vectors too
Shared_DataContainer Class for data.table Shared Between Tasks
sl3OptionsQuerying/setting a single 'sl3' option
sl3_TaskDefine a Machine Learning Task
StackLearner Stacking
SuperLearner_interfaceUse SuperLearner Wrappers, Screeners, and Methods, in sl3
true_obj_sizeEstimate object size using serialization
undocumented_learnerUndocumented Learner
variable_typeSpecify variable type
write_learner_templateGenerate a file containing a template 'sl3' Learner
jeremyrcoyle/sl3 documentation built on Sept. 8, 2018, 6:53 a.m.