@@ -61,7 +61,7 @@ function MMI.fit(model::LDA, ::Int, X, y)
6161 class_weights= MS. classweights (core_res),
6262 Sw= MS. withclass_scatter (core_res),
6363 Sb= MS. betweenclass_scatter (core_res),
64- nc = nc
64+ nclasses = nc
6565 )
6666 fitresult = (core_res, classes_seen)
6767 return fitresult, cache, report
@@ -226,7 +226,7 @@ function MMI.fit(model::BayesianLDA, ::Int, X, y)
226226 class_weights= MS. classweights (core_res),
227227 Sw= MS. withclass_scatter (core_res),
228228 Sb= MS. betweenclass_scatter (core_res),
229- nc = nc
229+ nclasses = nc
230230 )
231231
232232 fitresult = (core_res, classes_seen, priors, n)
@@ -359,7 +359,7 @@ function MMI.fit(model::SubspaceLDA, ::Int, X, y)
359359 projected_class_means= MS. classmeans (core_res),
360360 mean= MS. mean (core_res),
361361 class_weights= MS. classweights (core_res),
362- nc = nc
362+ nclasses = nc,
363363 )
364364 fitresult = (core_res, outdim, classes_seen)
365365 return fitresult, cache, report
@@ -459,7 +459,7 @@ function MMI.fit(model::BayesianSubspaceLDA, ::Int, X, y)
459459 projected_class_means= MS. classmeans (core_res),
460460 mean= MS. mean (core_res),
461461 class_weights= MS. classweights (core_res),
462- nc = nc
462+ nclasses = nc
463463 )
464464 fitresult = (core_res, outdim, classes_seen, priors, n, mult)
465465 return fitresult, cache, report
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