Defining A Task

sl3_Task make_sl3_Task()

Define a Machine Learning Task

Variable_Type variable_type()

Specify variable type

Finding Learners

sl3_list_properties() sl3_list_learners()

List sl3 Learners

sl3 Learners

Lrnr_HarmonicReg

Harmonic Regression

Lrnr_arima

Univariate ARIMA Models

Lrnr_bartMachine

BART Machine Learner

Lrnr_base make_learner()

Base Class for all sl3 Learners.

Lrnr_bilstm

Bidirectional Long short-term memory Recurrent Neural Network (LSTM)

Lrnr_condensier

Conditional Density Estimation

Lrnr_cv

Fit/Predict a learner with Cross Validation

Lrnr_dbarts

Discrete Bayesian Additive Regression Tree sampler

Lrnr_define_interactions

Define interactions terms

Lrnr_expSmooth

Exponential Smoothing

Lrnr_glm

Generalized Linear Models

Lrnr_glm_fast

Computationally Efficient GLMs

Lrnr_glmnet

GLMs with Elastic Net Regularization

Lrnr_grf

Generalized Random Forests Learner

define_h2o_X() Lrnr_h2o_glm

h2o Model Definition

Lrnr_h2o_grid Lrnr_h2o_classifier Lrnr_h2o_mutator

Grid Search Models with h2o

Lrnr_hal9001

The Scalable Highly Adaptive LASSO

Lrnr_independent_binomial

Classification from Binomial Regression

Lrnr_lstm

Long short-term memory Recurrent Neural Network (LSTM)

Lrnr_mean

Fitting Intercept Models

Lrnr_nnls

Non-negative Linear Least Squares

Lrnr_optim

Optimize Metalearner according to Loss Function using optim

Lrnr_pca

Principal Component Analysis and Regression

Lrnr_pkg_condensier_logisfitR6

sl3 Learner wrapper for condensier

Lrnr_randomForest

Random Forests

Lrnr_ranger

Ranger - A Fast Implementation of Random Forests

Lrnr_rpart

Learner for Recursive Partitioning and Regression Trees.

Lrnr_rugarch

Univariate GARCH Models

Lrnr_sl

SuperLearner Algorithm

Lrnr_solnp

Nonlinear Optimization via Augmented Lagrange

Lrnr_solnp_density

Nonlinear Optimization via Augmented Lagrange

Lrnr_stratified

Stratify learner fits by a single variable

Lrnr_subset_covariates

Learner with Covariate Subsetting

Lrnr_svm

Support Vector Machines

Lrnr_tsDyn

Nonlinear Time Series Analysis

Lrnr_xgboost

xgboost: eXtreme Gradient Boosting

Lrnr_pkg_SuperLearner Lrnr_pkg_SuperLearner_method Lrnr_pkg_SuperLearner_screener

Use SuperLearner Wrappers, Screeners, and Methods, in sl3

Composing Learners

Pipeline

Pipeline (chain) of learners.

Stack

Learner Stacking

Custom_chain customize_chain()

Customize chaining for a learner

Loss functions

loss_squared_error() loss_loglik_true_cat() loss_loglik_binomial() loss_loglik_multinomial()

Loss Function Definitions

risk()

Risk Esimation

Metalearner functions

metalearner_logistic_binomial() metalearner_linear() metalearner_linear_multinomial()

Combine predictions from multiple learners

Helpful for Defining Learners

write_learner_template()

Generate a file containing a template sl3 Learner

args_to_list()

Get all args of parent call (both specified and defaults) as list

call_with_args()

Call with filtered argument list

true_obj_size()

Estimate object size using serialization

safe_dim()

dim that works for vectors too

delayed_make_learner() learner_train() delayed_learner_train() learner_fit_predict() delayed_learner_fit_predict() learner_fit_chain() delayed_learner_fit_chain()

Learner helpers

Sample Datasets

cpp

Subset of growth data from the collaborative perinatal project (CPP)

cpp_1yr

Subset of growth data from the collaborative perinatal project (CPP)

bsds

Bicycle sharing time series dataset

density_dat

Simulated data with continuous exposure

Miscellaneous

sl3Options()

Querying/setting a single sl3 option

Index

Custom_chain customize_chain()

Customize chaining for a learner

Lrnr_HarmonicReg

Harmonic Regression

Lrnr_arima

Univariate ARIMA Models

Lrnr_bartMachine

BART Machine Learner

Lrnr_base make_learner()

Base Class for all sl3 Learners.

Lrnr_bilstm

Bidirectional Long short-term memory Recurrent Neural Network (LSTM)

Lrnr_condensier

Conditional Density Estimation

Lrnr_cv

Fit/Predict a learner with Cross Validation

Lrnr_dbarts

Discrete Bayesian Additive Regression Tree sampler

Lrnr_define_interactions

Define interactions terms

Lrnr_expSmooth

Exponential Smoothing

Lrnr_glm

Generalized Linear Models

Lrnr_glm_fast

Computationally Efficient GLMs

Lrnr_glmnet

GLMs with Elastic Net Regularization

Lrnr_grf

Generalized Random Forests Learner

define_h2o_X() Lrnr_h2o_glm

h2o Model Definition

Lrnr_h2o_grid Lrnr_h2o_classifier Lrnr_h2o_mutator

Grid Search Models with h2o

Lrnr_hal9001

The Scalable Highly Adaptive LASSO

Lrnr_independent_binomial

Classification from Binomial Regression

Lrnr_lstm

Long short-term memory Recurrent Neural Network (LSTM)

Lrnr_mean

Fitting Intercept Models

Lrnr_nnls

Non-negative Linear Least Squares

Lrnr_optim

Optimize Metalearner according to Loss Function using optim

Lrnr_pca

Principal Component Analysis and Regression

Lrnr_pkg_condensier_logisfitR6

sl3 Learner wrapper for condensier

Lrnr_randomForest

Random Forests

Lrnr_ranger

Ranger - A Fast Implementation of Random Forests

Lrnr_rpart

Learner for Recursive Partitioning and Regression Trees.

Lrnr_rugarch

Univariate GARCH Models

Lrnr_sl

SuperLearner Algorithm

Lrnr_solnp

Nonlinear Optimization via Augmented Lagrange

Lrnr_solnp_density

Nonlinear Optimization via Augmented Lagrange

Lrnr_stratified

Stratify learner fits by a single variable

Lrnr_subset_covariates

Learner with Covariate Subsetting

Lrnr_svm

Support Vector Machines

Lrnr_tsDyn

Nonlinear Time Series Analysis

Lrnr_xgboost

xgboost: eXtreme Gradient Boosting

Pipeline

Pipeline (chain) of learners.

Shared_Data

Container Class for data.table Shared Between Tasks

Stack

Learner Stacking

Lrnr_pkg_SuperLearner Lrnr_pkg_SuperLearner_method Lrnr_pkg_SuperLearner_screener

Use SuperLearner Wrappers, Screeners, and Methods, in sl3

args_to_list()

Get all args of parent call (both specified and defaults) as list

bsds

Bicycle sharing time series dataset

cpp

Subset of growth data from the collaborative perinatal project (CPP)

cpp_1yr

Subset of growth data from the collaborative perinatal project (CPP)

debug_train() debugonce_train() debug_predict() debugonce_predict() sl3_debug_mode() undebug_learner()

Helper functions to debug sl3 Learners

density_dat

Simulated data with continuous exposure

factor_to_indicators() dt_expand_factors()

Convert Factors to indicators

delayed_make_learner() learner_train() delayed_learner_train() learner_fit_predict() delayed_learner_fit_predict() learner_fit_chain() delayed_learner_fit_chain()

Learner helpers

sl3_list_properties() sl3_list_learners()

List sl3 Learners

loss_squared_error() loss_loglik_true_cat() loss_loglik_binomial() loss_loglik_multinomial()

Loss Function Definitions

make_learner_stack()

Make a stack of sl3 learners

metalearner_logistic_binomial() metalearner_linear() metalearner_linear_multinomial()

Combine predictions from multiple learners

pack_predictions() unpack_predictions()

Pack multidimensional predictions into a vector (and unpack again)

predict_classes()

Predict Class from Predicted Probabilities

prediction_plot()

Plot predicted and true values for diganostic purposes

risk()

Risk Esimation

safe_dim()

dim that works for vectors too

sl3Options()

Querying/setting a single sl3 option

sl3_Task make_sl3_Task()

Define a Machine Learning Task

true_obj_size()

Estimate object size using serialization

undocumented_learner

Undocumented Learner

Variable_Type variable_type()

Specify variable type

write_learner_template()

Generate a file containing a template sl3 Learner