as_mild_df |
Coerce to MILD data frame |
as_mi_df |
Coerce to MI data frame |
bag_instance_sampling |
Sample 'mild_df' object by bags and instances |
build_fm |
Build a feature map on new data |
build_fm.kfm_exact |
Build a feature map on new data |
build_fm.kfm_nystrom |
Build a feature map on new data |
build_instance_feature |
Flatten 'mild_df' data to the instance level |
classify_bags |
Classify y from bags |
cv_misvm |
Fit MI-SVM model to the data using cross-validation |
cv_misvm.default |
Fit MI-SVM model to the data using cross-validation |
cv_misvm.formula |
Fit MI-SVM model to the data using cross-validation |
cv_misvm.mi_df |
Fit MI-SVM model to the data using cross-validation |
formatting |
Printing multiple instance data frames |
generate_mild_df |
Generate mild_df using multivariate t and normal distributions. |
kfm_exact |
Create an exact kernel feature map |
kfm_nystrom |
Fit a Nyström kernel feature map approximation |
kfm_nystrom.default |
Fit a Nyström kernel feature map approximation |
kfm_nystrom.mild_df |
Fit a Nyström kernel feature map approximation |
kme |
Calculate the kernel mean embedding matrix |
kme.default |
Calculate the kernel mean embedding matrix |
kme.mild_df |
Calculate the kernel mean embedding matrix |
mi |
Create an 'mi' object |
mild |
Create a mild object |
mild_df |
Build a MILD data frame |
mior |
Fit MIOR model to the data |
mior.default |
Fit MIOR model to the data |
mior.formula |
Fit MIOR model to the data |
mior.mi_df |
Fit MIOR model to the data |
mismm |
Fit MILD-SVM model to the data |
mismm.default |
Fit MILD-SVM model to the data |
mismm.formula |
Fit MILD-SVM model to the data |
mismm.mild_df |
Fit MILD-SVM model to the data |
misvm |
Fit MI-SVM model to the data |
misvm.default |
Fit MI-SVM model to the data |
misvm.formula |
Fit MI-SVM model to the data |
misvm.mild_df |
Fit MI-SVM model to the data |
misvm.mi_df |
Fit MI-SVM model to the data |
misvm_orova |
Fit MI-SVM model to ordinal outcome data using One-vs-All |
misvm_orova.default |
Fit MI-SVM model to ordinal outcome data using One-vs-All |
misvm_orova.formula |
Fit MI-SVM model to ordinal outcome data using One-vs-All |
misvm_orova.mi_df |
Fit MI-SVM model to ordinal outcome data using One-vs-All |
mi_df |
Build a multiple instance (MI) data frame |
omisvm |
Fit MI-SVM-OR model to ordinal outcome data |
omisvm.default |
Fit MI-SVM-OR model to ordinal outcome data |
omisvm.formula |
Fit MI-SVM-OR model to ordinal outcome data |
omisvm.mi_df |
Fit MI-SVM-OR model to ordinal outcome data |
ordmvnorm |
Sample ordinal MIL data using mvnorm |
predict.cv_misvm |
Predict method for 'cv_misvm' object |
predict.mior |
Predict method for 'mior' object |
predict.mismm |
Predict method for 'mismm' object |
predict.misvm |
Predict method for 'misvm' object |
predict.misvm_orova |
Predict method for 'misvm_orova' object |
predict.omisvm |
Predict method for 'omisvm' object |
predict.smm |
Predict method for 'smm' object |
predict.svor_exc |
Predict method for 'svor_exc' object |
print.mild_df |
Printing multiple instance data frames |
print.mi_df |
Printing multiple instance data frames |
smm |
Fit SMM model to the data |
smm.default |
Fit SMM model to the data |
smm.formula |
Fit SMM model to the data |
smm.mild_df |
Fit SMM model to the data |
summarize_samples |
Summarize data across functions |
summarize_samples.default |
Summarize data across functions |
summarize_samples.mild_df |
Summarize data across functions |
svor_exc |
Fit SVOR-EXC model to ordinal outcome data |
svor_exc.default |
Fit SVOR-EXC model to ordinal outcome data |
svor_exc.formula |
Fit SVOR-EXC model to ordinal outcome data |
svor_exc.mi_df |
Fit SVOR-EXC model to ordinal outcome data |