README.md
In MarkusBonsch/mxLSTM: LSTM model for regression
mxLSTM
LSTM models for regression analysis with mxNet.
Features
Based on the excellent example here.
Added following features:
- takes numeric inputs instead of text (for timeseries regression)
- zoneout as described in Krueger et al. 2017 "Zoneout: Regularizing RNNs by randomly preserving hidden activations".
- batch normalization as described in T. Cooljmans et al. ILRC 2017 "Recurrent batch normalization".
- choice of different activation functions.
MarkusBonsch/mxLSTM documentation built on May 28, 2019, 6:40 a.m.
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mxLSTM
LSTM models for regression analysis with mxNet.
Features
Based on the excellent example here.
Added following features: - takes numeric inputs instead of text (for timeseries regression) - zoneout as described in Krueger et al. 2017 "Zoneout: Regularizing RNNs by randomly preserving hidden activations". - batch normalization as described in T. Cooljmans et al. ILRC 2017 "Recurrent batch normalization". - choice of different activation functions.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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