List with 100 random values for binary classfication It contains a list with x and y values. x.has 100 instances and 30 features. y is a vector of 100 binary (1 and 0) values. This dataset is for test plus classification.
Data frame with 5990 abstracts. Each abstract belongs to one of both classes, positive and unknown. Abstracts from parasite class are from ZOVER and GMPD database. Abstracs from unknown class are random abstracts retrived from crossref.
Data frame with 600 abstracts. Each abstract belongs to one of both classes, positive and unknown. Abstracts from parasite class are from ZOVER and GMPD database. Abstracs from unknown class are random abstracts retrived from crossref.
make predictions from a "plus" object. This function makes predictions from plus object. Is in essence a cross-validated glmnet model, optimized with the plus algorithm. It use the optimal value chosen for lambda for a fit.