Multiple-Instance Learning with Support Vector Machines

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Documentation for package ‘mildsvm’ version 0.4.0

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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