- Reflexive
$x R x$ , irreflexive, neither reflecive nor irreflexive (Sometimes reflexive, sometimes not depends on$x$ ) - Symmetricity
$a R b \implies b R a$
- Average length
- Cluster factor (How well connected are neighbors of
$n_i$ )
In general you can expect tf.nn.sparse_softmax_cross_entropy_with_logits
to be way better optimized because it processes logits directly instead of just applying xent to a probability distribution. Good news: it's trivial to use in Keras, when you need it.
set-option -g prefix C-a | |
bind-key C-a last-window | |
set -s escape-time 0 |