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<img src="https://static.igem.org/mediawiki/2017/archive/2/20/20170929214604%21T--Florida_Atlantic--owlbanner.png"> | <img src="https://static.igem.org/mediawiki/2017/archive/2/20/20170929214604%21T--Florida_Atlantic--owlbanner.png"> | ||
− | + | <div align='justify'> | |
<div class="column full_size"> | <div class="column full_size"> | ||
<h3 style=" font-size:24px ; ">Model</h3> | <h3 style=" font-size:24px ; ">Model</h3> | ||
<center><h4>LSTM Machine Learning Model</h4></center> | <center><h4>LSTM Machine Learning Model</h4></center> | ||
− | <p>The LSTM model contained two lstm layers | + | <p font-size='18px'>The LSTM model contained two lstm layers |
with 300 nodes each. The first lstm layer used dropout with a dropout | with 300 nodes each. The first lstm layer used dropout with a dropout | ||
probability of 0.5 to avoid overfitting the training data. The third | probability of 0.5 to avoid overfitting the training data. The third |
Revision as of 14:42, 1 November 2017
Florida_Atlantic
Model
LSTM Machine Learning Model
The LSTM model contained two lstm layers with 300 nodes each. The first lstm layer used dropout with a dropout probability of 0.5 to avoid overfitting the training data. The third layer of the network was a fully-connected layer with 150 nodes and hyperbolic tangent activation function. The output layer contained two nodes with a softmax activation function./