0 ×

**KNIME Deep Learning - Keras Integration** version **4.1.0.v201911110939** by **KNIME AG, Zurich, Switzerland**

Exponential linear units were introduced to alleviate the disadvantages of
ReLU and LeakyReLU units, namely to push the mean activation closer to zero while
still saturating to a negative value which increases robustness against noise if the unit is
in an off state (i.e. the input is very negative).
The formula is `f(x) = alpha * (exp(x) - 1) for x < 0 and f(x) = x for x >= 0`

.
For the exact details see the corresponding paper.
Corresponds to the
Keras ELU Layer.

- Name prefix
- The name prefix of the layer. The prefix is complemented by an index suffix to obtain a unique layer name. If this option is unchecked, the name prefix is derived from the layer type.
- Alpha
- Scale for the negative factor of the exponential linear unit.

- Keras Network Reader (50 %)
- DL Python Network Creator (50 %)

- Keras Network Learner (100 %)

To use this node in KNIME, install KNIME Deep Learning - Keras Integration from the following update site:

KNIME 4.1

You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.

Do you have feedback, questions, comments about NodePit, want to support this platform, or want your own nodes or workflows listed here as well? Do you think, the search results could be improved or something is missing? Then please get in touch! Alternatively, you can send us an email to mail@nodepit.com, follow @NodePit on Twitter, or chat on Gitter!

Please note that this is only about NodePit. We do not provide general support for KNIME — please use the KNIME forums instead.