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Model prediction

Source: R/DFA_class.R, R/PCA_class.R, R/PLSR_class.R, and 20 more
model_predict.Rd

Apply a model using the input DatasetExperiment. Assumes the model is trained first.

Usage

# S4 method for class 'DFA,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'PCA,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'PLSR,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'PLSDA,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'autoscale,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'blank_filter,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'constant_sum_norm,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'dratio_filter,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'filter_by_name,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'filter_na_count,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'filter_smeta,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'glog_transform,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'linear_model,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'mean_centre,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'mv_feature_filter,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'mv_sample_filter,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'OPLSR,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'OPLSDA,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'pareto_scale,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'pqn_norm,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'SVM,DatasetExperiment'
model_predict(M, D)

# S4 method for class 'vec_norm,DatasetExperiment'
model_predict(M, D)

Arguments

M

a model object

D

a DatasetExperiment object

Value

Returns a modified model object

Examples

M = example_model()
M = model_predict(M,iris_DatasetExperiment())