gauss_cat_loss function

A torch::nn_module() Representing a gauss_cat_loss

The gauss_cat_loss module layer computes the log probability of the groundtruth for each object given the mask and the distribution parameters. That is, the log-likelihoods of the true/full training observations based on the generative distributions parameters distr_params inferred by the masked versions of the observations.

gauss_cat_loss(one_hot_max_sizes, min_sigma = 1e-04, min_prob = 1e-04)

Arguments

• one_hot_max_sizes: A torch tensor of dimension n_features containing the one hot sizes of the n_features

  features. That is, if the ith feature is a categorical feature with 5 levels, then one_hot_max_sizes[i] = 5. While the size for continuous features can either be 0 or 1.

• min_sigma: For stability it might be desirable that the minimal sigma is not too close to zero.

• min_prob: For stability it might be desirable that the minimal probability is not too close to zero.

Details

Note that the module works with mixed data represented as 2-dimensional inputs and it works correctly with missing values in groundtruth as long as they are represented by NaNs.

Author(s)

Lars Henry Berge Olsen