LKT: LKT
In LKT: Logistic Knowledge Tracing

LKT	R Documentation

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 :