RotMatPPO {ODRF}

Create a Projection Matrix: RotMatPPO

Description

Create a projection matrix using projection pursuit optimization (PPO).

Usage

RotMatPPO(
  X,
  y,
  model = "PPR",
  split = "entropy",
  weights = NULL,
  dimProj = min(ceiling(length(y)^0.4), ceiling(ncol(X) * 2/3)),
  numProj = ifelse(dimProj == "Rand", sample(floor(ncol(X)/3), 1),
    ceiling(ncol(X)/dimProj)),
  catLabel = NULL,
  ...
)

Arguments

X

An n by d numeric matrix (preferable) or data frame.

y

A response vector of length n.

model

Model for projection pursuit (for details see PPO).

split

One of three criteria, 'gini': gini impurity index (classification), 'entropy': information gain (classification, default) or 'mse': mean square error (regression).

weights

A vector of length same as data that are positive weights. (default NULL)

dimProj

Number of variables to be projected, dimProj=min(ceiling(n^0.4),ceiling(ncol(X)*2/3)) (default) or dimProj="Rand": random from 1 to ncol(X).

numProj

The number of projection directions, when dimProj="Rand" default numProj = sample(ceiling(ncol(X)/3),1) otherwise default numProj=ceiling(ncol(X)/dimProj).

catLabel

A category labels of class list in predictors. (default NULL, for details see Examples of ODT)

...

Used to handle superfluous arguments passed in using paramList.

Value

A random matrix to use in running ODT.

• Variable: Variables to be projected.

• Number: Number of projections.

• Coefficient: Coefficients of the projection matrix.

See Also

RotMatMake RotMatRand RotMatRF PPO

Examples

set.seed(220828)
X <- matrix(rnorm(1000), 100, 10)
y <- (rnorm(100) > 0) + 0
(RotMat <- RotMatPPO(X, y))
(RotMat <- RotMatPPO(X, y, dimProj = "Rand"))
(RotMat <- RotMatPPO(X, y, dimProj = 6, numProj = 4))

# classification
data(seeds)
(PP <- RotMatPPO(seeds[, 1:7], seeds[, 8], model = "Log", split = "entropy"))
(PP <- RotMatPPO(seeds[, 1:7], seeds[, 8], model = "PPR", split = "entropy"))
(PP <- RotMatPPO(seeds[, 1:7], seeds[, 8], model = "LDA", split = "entropy"))

# regression
data(body_fat)
(PP <- RotMatPPO(body_fat[, 2:15], body_fat[, 1], model = "Log", split = "mse"))
(PP <- RotMatPPO(body_fat[, 2:15], body_fat[, 1], model = "Rand", split = "mse"))
(PP <- RotMatPPO(body_fat[, 2:15], body_fat[, 1], model = "PPR", split = "mse"))