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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