7bcc6cd27df8b683a9d35e30fde5c61c *DESCRIPTION
c97acc758a1ab549f2f334515f44f967 *NAMESPACE
0c82174b70d822538ef3df2614bc7cc9 *NEWS.md
35168a052f8783c28a863ca351b20296 *R/lilikoi.KEGGplot.R
cf16e626e533e6f1387d8454cdac298d *R/lilikoi.Loaddata.r
033812180819e693ed27d45a2f680b69 *R/lilikoi.MetaTOpathway.r
61f90a2e2aee31cbf12a604086315ff0 *R/lilikoi.PDSfun.r
92ab9c50ae51ec986a838973aabc89b8 *R/lilikoi.explr.R
af0dd305e2a44e3b307dbb46767f2a62 *R/lilikoi.featuresSelection.r
bdfa0fc853b3f63b189de8325db46962 *R/lilikoi.globals.R
661294acdc86b3deb56097277b9689ca *R/lilikoi.machine_learning.r
20ba9b8df38e9e94709cdb8798482cd8 *R/lilikoi.meta_path.R
049761b9bba611ca53c8e200f08c761a *R/lilikoi.preproc_knn.R
85df50aae48e32ae24e262f2870e9440 *R/lilikoi.preproc_norm.R
91fbf424d86b2bbc5572e1f441e26618 *R/lilikoi.prognosis.R
895e8914285b2a0642939ef745707d44 *R/sysdata.rda
45660a8ec714a42aadb24b909ae616b6 *README.md
1a484844dcb65f1133825f1ed4980e77 *build/vignette.rds
662cd25d1e2f718589879a0b9f325fda *inst/L2cross.py
37a1a68b3177ac11d117ed695b97b647 *inst/L2cross_nopercent.py
cf2e7d2b2f0f0c4738efda6a187ae5e8 *inst/cox_nnet3/__init__.py
156e01b2a5eb1ebd24bce617c7f89fb8 *inst/cox_nnet3/__pycache__/__init__.cpython-36.pyc
c05b8db5b5ae93bb030f6afd86e01301 *inst/cox_nnet3/__pycache__/cox_nnet.cpython-36.pyc
ee263c2e10feb0fdf4190c37d3839a3a *inst/cox_nnet3/__pycache__/cox_nnet3.cpython-36.pyc
2f5de85d55c9fdbcdec0fa82192c68a6 *inst/cox_nnet3/cox_nnet3.py
669fd2702a007ba0a1c57f5c0560020d *inst/doc/Vignette.R
8c7a8947c927a18fb5778a20e0c8d5d3 *inst/doc/Vignette.Rmd
c0991a0ba26c7ba1e6ac8965aaeeb04c *inst/doc/Vignette.html
dea28d25b12d07d4a3c2e2be89f13b97 *inst/extdata/data_format.csv
0d586f6c79e276ba9ca3d99a72dfa416 *inst/extdata/plasma_breast_cancer.csv
ec0495eca8de8d48f94e889c3c739f64 *inst/extdata/plasma_breast_cancer_Meta.csv
0d586f6c79e276ba9ca3d99a72dfa416 *inst/extdata/plasma_breast_cancer_data.csv
065b34cec505638b3a6cdf668ac7c390 *man/lilikoi.KEGGplot.Rd
681fcac0407b546468b6437eef00001d *man/lilikoi.Loaddata.Rd
470863223de939f4d8e6f5c4d47bca52 *man/lilikoi.MetaTOpathway.Rd
24ecb4360e88c4ed3f8bf447ffc9f9ab *man/lilikoi.PDSfun.Rd
c173bf84b940c42d741b849ec6c3146e *man/lilikoi.explr.Rd
31d24e4dff33132ed3d212b6641f90fd *man/lilikoi.featuresSelection.Rd
8b03f2e23b4cbd04f3fcbaa7371fdf26 *man/lilikoi.machine_learning.Rd
fcc6f829e951e03aba96517ba5ee70c4 *man/lilikoi.meta_path.Rd
9d4b8a9336f9c5ecb2a05bd4708df3db *man/lilikoi.preproc_knn.Rd
db5af66b7193713da7663a68bbf32f53 *man/lilikoi.preproc_norm.Rd
8cab29b09b26354fe0fc943d882d1824 *man/lilikoi.prognosis.Rd
8c7a8947c927a18fb5778a20e0c8d5d3 *vignettes/Vignette.Rmd
