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**KNIME Deep Learning - Keras Integration** version **4.2.1.v202008251157** 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 Input Layer (34 %)
- DL Python Network Creator (24 %)
- Keras Network Reader (14 %)
- Keras Network Learner (10 %)
- Keras Batch Normalization Layer (7 %)
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- Keras Network Learner (29 %)
- Keras Dense Layer (21 %)
~~DL Network Executor~~(4 %) StreamableDeprecated- Keras Network Writer (4 %)
- Keras Softmax Layer (4 %)
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To use this node in KNIME, install KNIME Deep Learning - Keras Integration from the following update site:

KNIME 4.2

A zipped version of the software site can be downloaded here.

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