LKT {LKT}

LKT

Description

Compute a logistic regression model of learning for input data.

Usage

LKT(
  data,
  usefolds = NA,
  components,
  features,
  fixedpars = NA,
  seedpars = NA,
  interacts = NA,
  curvefeats = NA,
  dualfit = FALSE,
  interc = FALSE,
  verbose = TRUE,
  epsilon = 1e-04,
  cost = 512,
  lowb = 1e-05,
  highb = 0.99999,
  type = 0,
  maketimes = FALSE,
  bias = 0,
  maxitv = 100,
  factrv = 1e+12,
  nosolve = FALSE,
  autoKC = rep(0, length(components)),
  autoKCcont = rep("NA", length(components)),
  connectors = rep("+", max(1, length(components) - 1))
)

Arguments

data

A dataset with Anon.Student.Id and CF..ansbin.

usefolds

Numeric Vector | Specifies the folds for model fitting in LKT; the features are still calculated across all folds to compute test fold fit externally

components

A vector of factors that can be used to compute each features for each subject.

features

a vector methods to use to compute a feature for the component.

fixedpars

a vector of parameters for all features+components.

seedpars

a vector of parameters for all features+components to seed non-linear parameter search.

interacts

A list of components that interacts with component by feature in the main specification.

curvefeats

vector of columns to use with "diff" functions

dualfit

TRUE or FALSE, fit a simple latency using logit. Requires Duration..sec. column in data.

interc

TRUE or FALSE, include a global intercept.

verbose

provides more output in some cases.

epsilon

passed to LiblineaR

cost

passed to LiblineaR

lowb

lower bound for non-linear optimizations

highb

upper bound for non-linear optimizations

type

passed to LiblineaR

maketimes

Boolean indicating whether to create time based features (or may be precomputed)

bias

passed to LiblineaR

maxitv

passed to nonlinear optimization a maxit control

factrv

controls the optim() function

nosolve

causes the function to return a sparse data matrix of the features, rather than a solution

autoKC

a vector to indicate whether to use autoKC for the component (0) or the k for the numebr of clusters

autoKCcont

a vector of text strings set to "rand" for component to make autoKC assignment to cluster is randomized (for comaprison)

connectors

a vector if linear equation R operators including +, * and :

Value

list of values "model", "coefs", "r2", "prediction", "nullmodel", "latencymodel", "optimizedpars","subjectrmse", "newdata", and "automat"