# Fusing Machine Learning in R

## Documentation for package ‘fuseMLR’ version 0.0.4

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

bestLayerLearner | The best layer-specific model is used as meta model.
cobra | Cobra Meta Learner
createCobraPred | Create COBRA Predictions
createDif | Create Difference
createLoss | Create Loss
createTesting | createTesting
createTestLayer | createTestLayer
createTraining | createTraining
createTrainLayer | createTrainLayer
createTrainMetaLayer | createTrainMetaLayer
createWeights | Create weights for COBRA Predictions
Data | Abstract class Data
extractData | extractData
extractModel | extractModel
fusemlr | fusemlr
HashTable | Class HashTable
Lrner | Lrner Class
Model | Model Class
multi_omics | Simulated multiomics data for 70 training participants and 23 testing participants, each with an effect size of 20 on each layer. Each layer includes 50 participants for training and 20 for testing. Participants do not perfectly overlap across layers. The simulation is based on the R package 'interSIM'.
predict.bestLayerLearner | Best specific Learner prediction.
predict.cobra | Predict Using COBRA object
predict.Training | predict.Training
predict.weightedMeanLearner | Weighted mean prediction.
PredictData | PredictData Class
Predicting | Predicting Class
PredictLayer | PredictLayer Class
PredictMetaLayer | PredictMetaLayer Class
summary.Testing | Testing object Summaries
summary.Training | Training object Summaries
Target | Target Class
TestData | TestData Class
Testing | Testing Class
TestLayer | TestLayer Class
TestMetaLayer | TestMetaLayer Class
TrainData | TrainData Class
Training | Training Class
TrainLayer | TrainLayer Class
TrainMetaLayer | TrainMetaLayer Class
upsetplot | upsetplot
VarSel | Varsel Class
varSelection | varSelection
weightedMeanLearner | The weighted mean meta-learner