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Hypothesis wrapper for functional models

Hypothesis.Rd

Construct a hypothesis object that wraps a user-supplied function with minimal metadata so it can be visualized like a learner.

R6 class wrapping a user-supplied function plus minimal metadata so it can be visualized like a learner on 1D or 2D inputs.

Usage

hypothesis(
  fun,
  type,
  predictors,
  link = "identity",
  domain = NULL,
  levels = NULL
)

Arguments

fun

(function) Function defining the hypothesis. Accepted signatures:

  • 1D: fun(x, ...) or fun(data) where data is a data.frame with one predictor column

  • 2D: fun(x, y, ...) or fun(data) where data is a data.frame with two predictor columns

type

(character(1)) One of "regr" or "classif".

predictors

(character()) Names of the predictor columns. Length must be 1 or 2.

(character(1)) Link for classif outputs: "identity" (default) or "logit". For regression, only "identity" is used.

domain

(list|NULL) Named list with limits per predictor, e.g., list(x = c(-3, 3)) for 1D or list(x = c(-3,3), y = c(-3,3)) for 2D. Used when no Task is provided.

levels

(character(2)|NULL) Class labels for binary classification.

Value

An R6 Hypothesis object with a predict(newdata) method.

Public fields

fun

(function) User-provided function implementing the hypothesis.

type

(character(1)) Prediction type, one of "regr" or "classif".

predictors

(character()) Names of predictor columns (length 1 or 2).

input_dim

(integer(1)) Number of predictors, derived from predictors.

link

(character(1)) Link for classif output: "identity" or "logit".

domain

(list|NULL) Named list with limits per predictor for plotting without a Task.

levels

(character(2)|NULL) Class labels for binary classification.

Methods

Public methods

Method new()

Create a new Hypothesis instance

Usage

Hypothesis$new(
  fun,
  type,
  predictors,
  link = "identity",
  domain = NULL,
  levels = NULL
)

Arguments

fun

(function) See class field fun.

type

(character(1)) See class field type.

predictors

(character()) See class field predictors.

link

(character(1)) See class field link.

domain

(list|NULL) See class field domain.

levels

(character(2)|NULL) See class field levels.

Method predict()

Predict on newdata

Usage

Hypothesis$predict(newdata)

Arguments

newdata

(data.frame) with columns matching predictors in order

Returns

numeric vector of predictions (regression) or probabilities in \([0, 1]\) (classification)

Method clone()

The objects of this class are cloneable with this method.

Usage

Hypothesis$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.