Predict with a Trained MaxEnt Model — maxent_predict_model • maxentcpp

Computes raw Gibbs distribution scores for new environmental data, using the feature lambdas stored in the trained FeaturedSpace.

Usage

maxent_predict_model(featured_space, newdata)

Arguments

featured_space: External pointer to a trained FeaturedSpace object.
newdata: Numeric matrix: one row per new point, one column per feature. Column values must be the already-evaluated feature values (e.g., from running maxent_feature_eval() for each feature and each point).

Value

Numeric vector of raw (unnormalized) prediction scores.

Examples

if (FALSE) { # \dontrun{
# After training, predict on 5 new points with 2 features each
newdata <- matrix(runif(10), nrow = 5, ncol = 2)
preds <- maxent_predict_model(fs, newdata)
} # }