fits <- lapply(models, function(model){ 
  print(model)
  train(y ~ ., method = model, data = mnist_27$train)
}) 

names(fits) <- models

[1] "glm"
[1] "lda"
[1] "naive_bayes"
[1] "svmLinear"
[1] "knn"
[1] "gamLoess"
[1] "multinom"
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 363.006381
iter  10 value 363.006380
iter  10 value 363.006380
final  value 363.006380 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 404.062761
iter  10 value 404.062761
iter  10 value 404.062761
final  value 404.062761 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 363.068935
iter  10 value 363.068933
iter  10 value 363.068933
final  value 363.068933 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 360.141150
iter  10 value 360.141147
iter  10 value 360.141146
final  value 360.141146 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 400.093399 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 360.200965
iter  10 value 360.200962
iter  10 value 360.200961
final  value 360.200961 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 368.331484 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 406.483080 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 368.387268 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 326.060854
final  value 326.060812 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 375.809021
iter  10 value 375.809021
iter  10 value 375.809021
final  value 375.809021 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 326.139752
final  value 326.139710 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 383.937418
iter  10 value 383.937417
iter  10 value 383.937416
final  value 383.937416 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 418.402234 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 383.987483
iter  10 value 383.987481
iter  10 value 383.987480
final  value 383.987480 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 327.620057
final  value 327.618901 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 377.133976 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 327.698706
final  value 327.697535 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 396.912731 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 429.503204 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 396.959590 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 361.679549
iter  10 value 361.679548
iter  10 value 361.679548
final  value 361.679548 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 403.835738 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 361.743401
iter  10 value 361.743400
iter  10 value 361.743400
final  value 361.743400 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 376.734538
final  value 376.734532 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 415.655694 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 376.792839
final  value 376.792834 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 369.060407
iter  10 value 369.060407
iter  10 value 369.060407
final  value 369.060407 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 409.498977 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 369.121542
iter  10 value 369.121542
iter  10 value 369.121542
final  value 369.121542 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 380.358458 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 415.137514 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 380.408789 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 352.175122
final  value 352.175109 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 402.468163 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 352.256825
final  value 352.256812 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 373.678632 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 410.825521 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 373.733085 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 385.262518
iter  10 value 385.262518
iter  10 value 385.262518
final  value 385.262518 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 419.818784 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 385.312579
iter  10 value 385.312579
iter  10 value 385.312579
final  value 385.312579 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 358.781631 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 401.509013 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 358.846811 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 365.236209
final  value 365.236147 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 408.809532 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 365.303936
final  value 365.303879 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 385.061911 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 420.497959 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 385.112885 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 361.068426
final  value 361.068418 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 399.866227 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 361.126015
final  value 361.126007 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 341.206831
iter  10 value 341.206829
iter  10 value 341.206829
final  value 341.206829 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 386.341663 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 341.275177
iter  10 value 341.275175
iter  10 value 341.275174
final  value 341.275174 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 347.565140
final  value 347.564979 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 391.589434
iter  10 value 391.589433
iter  10 value 391.589433
final  value 391.589433 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 347.632355
final  value 347.632196 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 371.125281
final  value 371.117862 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 407.432975 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 371.178536
final  value 371.171169 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 334.074150
final  value 333.573350 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 382.769285 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 334.149322
final  value 333.651868 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 348.548206
final  value 348.548187 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 394.231579 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 348.619259
final  value 348.619241 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 371.438914 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 412.807549 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 371.501382 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 342.860743
final  value 342.860724 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 387.525234 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
iter  10 value 342.928461
final  value 342.928443 
converged
# weights:  4 (3 variable)
initial  value 554.517744 
final  value 401.160559 
converged
[1] "qda"
[1] "rf"
note: only 1 unique complexity parameters in default grid. Truncating the grid to 1 .

[1] "adaboost"