Fit a plus model to an abstracts object

Usage

fit_plus(
  abstracts,
  vocabulary = NULL,
  tf_idf = TRUE,
  alpha = 1,
  sample_use_time = 30,
  learning_rate = 1,
  qq = 0.1
)

Arguments

abstracts: An abstracts object.
vocabulary: A ext2vec_vocabulary object from a specific corpus to create a document - term matrix.
tf_idf: Logical. Default is true, use a tf_idf in the document - term matrix S
alpha: Plus parameter. The elastic net mixing parameter, with \(0\le\alpha\le 1\)
sample_use_time: Plus parameter. Number of use time.
learning_rate: Plus parameter. Learning rate. Default is 1.
qq: Plus parameter. quantile threshold

Value

Return a plus object.(Positive and unlabeled Learning from Unbalanced cases and Sparse structures, PLUS). This is a cross-validated glmnet logistics regression optimized for positive and unlabeled learning. This classification is applied to a dtm matrix created with the vocabulary and the abstracts. The independent variables are the possitive and unknown classes of the provided abstract object.

Examples

abstracts <- get_abstracts(lacsSample)
v <- get_vocabulary(abstracts, term_count = 2)
s <- sample(seq(nrow(abstracts)), 65, replace = FALSE)
train <- abstracts[s, ]
model <- fit_plus(abstracts = train, vocabulary = v)
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: no non-missing arguments to min; returning Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: one multinomial or binomial class has fewer than 8  observations; dangerous ground
#> Warning: Too few (< 10) observations per fold for type.measure='auc' in cv.lognet; changed to type.measure='deviance'. Alternatively, use smaller value for nfolds
#> Warning: no non-missing arguments to max; returning -Inf
model
#> 
#> Call:  glmnet::cv.glmnet(x = train.X, y = y, family = "binomial") 
#> 
#> Measure: Binomial Deviance 
#> 
#>     Lambda Index Measure      SE Nonzero
#> min 0.1163    12   1.288 0.03285       9
#> 1se 0.1277    10   1.306 0.03029       8