Optimal Learning Lab

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Reference

Input parameters and output values used in typical LKT workflows.

Reference guide to common input parameters and output values in LKT workflows.

Inputs

Common input parameters

These names follow the LKT 1.7.0 reference manual, checked October 13, 2026. Consult the manual for complete arguments and version-specific behavior.

Data and structure

  • data: dataset with Anon.Student.Id and CF..ansbin. columns
  • components: factors used to compute features per subject
  • features: methods used to compute those features
  • curvefeats: columns used with difference-style functions
  • connectors: linear-equation operators such as +, *, and :

Fitting and optimization

  • usefolds: folds selected for fitting; features are calculated across all folds
  • fixedpars and seedpars: parameter vectors used in fitting and initialization
  • epsilon, cost, type, bias: solver-related settings
  • lowb, highb, maxitv, factrv: optimization controls
  • dualfit, interc, verbose, nosolve: behavior flags
Outputs

Common returned values

Model objects and fit

  • model: the fitted logistic regression model
  • nullmodel: intercept-only baseline model
  • coefs: fitted coefficients
  • r2: pseudo R-squared style fit measure
  • optimizedpars: optimized parameters from fitting

Predictions and derived outputs

  • prediction: model predictions
  • latencymodel: latency-related model if dual fitting is enabled
  • subjectrmse: per-student prediction error summary
  • newdata: transformed or feature-enriched data
  • automat: an additional returned object listed in the manual; its interpretation depends on the model configuration