View source: R/model_list_class.R
model_seq | R Documentation |
A class for (ordered) lists of models
model_seq(...) ## S4 method for signature 'model_seq,DatasetExperiment' model_train(M, D) ## S4 method for signature 'model_seq,DatasetExperiment' model_predict(M, D) ## S4 method for signature 'model_seq,ANY,ANY,ANY' x[i] ## S4 replacement method for signature 'model_seq,ANY,ANY,ANY' x[i] <- value ## S4 method for signature 'model_seq' models(ML) ## S4 replacement method for signature 'model_seq,list' models(ML) <- value ## S4 method for signature 'model_seq' length(x) ## S4 method for signature 'model,model_seq' e1 + e2 ## S4 method for signature 'model_seq,model' e1 + e2 ## S4 method for signature 'model,model' e1 + e2 ## S4 method for signature 'model_seq' predicted(M) ## S4 method for signature 'model_seq,DatasetExperiment' model_apply(M, D)
... |
named slots and their values. |
M |
a model object |
D |
a dataset object |
x |
a model_seq object |
i |
index |
value |
value |
ML |
a model_seq object |
e1 |
a model or model_seq object |
e2 |
a model or model_seq object |
model sequence
model sequence
model at the given index in the sequence
model sequence with the model at index i replaced
a list of models in the sequence
a model sequence containing the input models
the number of models in the sequence
a model sequence with the additional model appended to the front of the sequence
a model sequence with the additional model appended to the end of the sequence
a model sequence
the predicted output of the last model in the sequence
MS = model_seq() MS = model() + model() MS = example_model() + example_model() MS = model_train(MS,DatasetExperiment()) D = DatasetExperiment() MS = example_model() + example_model() MS = model_train(MS,D) MS = model_predict(MS,D) MS = model() + model() MS[2] MS = model() + model() MS[3] = model() MS = model() + model() L = models(MS) MS = model_seq() L = list(model(),model()) models(MS) = L MS = model() + model() length(MS) # 2 MS = model() + model() M = model() MS = M + MS MS = model() + model() M = model() MS = MS + M MS = model() + model() D = DatasetExperiment() M = example_model() M = model_train(M,D) M = model_predict(M,D) p = predicted(M) D = DatasetExperiment() MS = example_model() + example_model() MS = model_apply(MS,D)
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