FeatureProcessor: Base class for all data processors

Abstract class for input/output processors used in rhealth. Subclass this to define how raw values (e.g. timestamps, labels) are transformed into model-ready tensors.

Methods to override

• process(value): Converts input value into tensor

• size(): Returns output dimensionality

Super class

RHealth::Processor -> FeatureProcessor

Methods

Public methods

• FeatureProcessor$fit()

• FeatureProcessor$process()

• FeatureProcessor$clone()

Inherited methods

• RHealth::Processor$load()
• RHealth::Processor$save()

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Method fit()

Fit processor using field values across samples.

Usage

FeatureProcessor$fit(samples, field)

Arguments

samples

A list of named lists representing sample records.

field

A string giving the field name to fit on.

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Method process()

Abstract method: Process an individual field value.

Usage

FeatureProcessor$process(value)

Arguments

value

A raw value (e.g., character, number, etc).

Returns

A processed value.

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Method clone()

The objects of this class are cloneable with this method.

Usage

FeatureProcessor$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.