MLearn-methods: The 'MLearn' interface for machine learning

In lgatto/pRoloc: A unifying bioinformatics framework for spatial proteomics

The MLearn interface for machine learning

Description

This method implements MLInterfaces' MLean method for instances of the class "MSnSet".

Methods

signature(formula = "formula", data = "MSnSet", .method = "learnerSchema", trainInd = "numeric")

The learning problem is stated with the formula and applies the .method schema on the MSnSet data input using the trainInd numeric indices as train data.

signature(formula = "formula", data = "MSnSet", .method = "learnerSchema", trainInd = "xvalSpec")

In this case, an instance of xvalSpec is used for cross-validation.

signature(formula = "formula", data = "MSnSet", .method = "clusteringSchema", trainInd = "missing")

Hierarchical (hclustI), k-means (kmeansI) and partitioning around medoids (pamI) clustering algorithms using MLInterface's MLearn interface.

See Also

The MLInterfaces package documentation, in particular MLearn.

lgatto/pRoloc documentation built on Oct. 23, 2024, 12:51 a.m.