Multiple-Instance Learning with Support Vector Machines

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Documentation for package ‘mildsvm’ version 0.4.0

• DESCRIPTION file.

Help Pages

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