rtModClass-class: 'rtemis' Classification Model Class

In egenn/rtemis: Machine Learning and Visualization

rtemis Classification Model Class

Description

rtemis Classification Model Class

rtemis Classification Model Class

Details

R6 Class for rtemis Classification Models

Super class

rtemis::rtMod -> rtModClass

Public fields

fitted.prob

Training set probability estimates

predicted.prob

Testing set probability estimates

Methods

Public methods

• rtModClass$new()

• rtModClass$plotROC()

• rtModClass$plotROCfitted()

• rtModClass$plotROCpredicted()

• rtModClass$plotPR()

• rtModClass$plotPRfitted()

• rtModClass$plotPRpredicted()

• rtModClass$clone()

Inherited methods

• rtemis::rtMod$describe()
• rtemis::rtMod$plot()
• rtemis::rtMod$plotFitted()
• rtemis::rtMod$plotFittedPredicted()
• rtemis::rtMod$plotPredicted()
• rtemis::rtMod$plotVarImp()
• rtemis::rtMod$print()
• rtemis::rtMod$summary()

---

Method new()

Initialize rtModClass object

Usage

rtModClass$new(
  mod.name = character(),
  y.train = numeric(),
  y.test = numeric(),
  x.name = character(),
  y.name = character(),
  xnames = character(),
  mod = list(),
  type = character(),
  gridsearch = NULL,
  parameters = list(),
  fitted = numeric(),
  fitted.prob = numeric(),
  se.fit = numeric(),
  error.train = list(),
  predicted = NULL,
  predicted.prob = NULL,
  se.prediction = NULL,
  error.test = NULL,
  varimp = NULL,
  question = character(),
  extra = list()
)

Arguments

mod.name

Character: Algorithm name

y.train

Training set output

y.test

Testing set output

x.name

Character: Feature set name

y.name

Character: Output name

xnames

Character vector: Feature names

mod

Trained model

type

Character: Type of model (Regression, Classification, Survival)

gridsearch

Grid search output

parameters

List of training parameters

fitted

Fitted values (training set predictions)

fitted.prob

Training set probability estimates

se.fit

Standard error of the fit

error.train

Training set error

predicted

Predicted values (Testing set predictions)

predicted.prob

Testing set probability estimates

se.prediction

Testting set standard error

error.test

Testing set error

varimp

Variable importance

question

Question the model is trying to answer

extra

List of extra model info

sessionInfo

R session info at time of training

---

Method plotROC()

plot ROC. Uses testing set if available, otherwise training

Usage

rtModClass$plotROC(theme = rtTheme, filename = NULL, ...)

Arguments

theme

Theme to pass to plotting function

filename

Character: Path to file to save plot

...

Extra arguments to pass to plotting function

---

Method plotROCfitted()

Plot training set ROC

Usage

rtModClass$plotROCfitted(
  main = "ROC Training",
  theme = rtTheme,
  filename = NULL,
  ...
)

Arguments

main

Character: Main title

theme

Theme to pass to plotting function

filename

Character: Path to file to save plot

...

Extra arguments to pass to plotting function

---

Method plotROCpredicted()

plot testing set ROC

Usage

rtModClass$plotROCpredicted(
  main = "ROC Testing",
  theme = rtTheme,
  filename = NULL,
  ...
)

Arguments

main

Character: Main title

theme

Theme to pass to plotting function

filename

Character: Path to file to save plot

...

Extra arguments to pass to plotting function

---

Method plotPR()

plot Precision-Recall curve. Uses testing set if available, otherwise training

Usage

rtModClass$plotPR(theme = rtTheme, filename = NULL, ...)

Arguments

theme

Theme to pass to plotting function

filename

Character: Path to file to save plot

...

Extra arguments to pass to plotting function

---

Method plotPRfitted()

Plot training set Precision-Recall curve.

Usage

rtModClass$plotPRfitted(
  main = "P-R Training",
  theme = rtTheme,
  filename = NULL,
  ...
)

Arguments

main

Character: Main title

theme

Theme to pass to plotting function

filename

Character: Path to file to save plot

...

Extra arguments to pass to plotting function

---

Method plotPRpredicted()

plot testing set Precision-Recall curve.

Usage

rtModClass$plotPRpredicted(
  main = "P-R Testing",
  theme = rtTheme,
  filename = NULL,
  ...
)

Arguments

main

Character: Main title

theme

Theme to pass to plotting function

filename

Character: Path to file to save plot

...

Extra arguments to pass to plotting function

---

Method clone()

The objects of this class are cloneable with this method.

Usage

rtModClass$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

egenn/rtemis documentation built on April 24, 2024, 6:58 p.m.