Update README.md

kasungayan · Mar 27, 2020 · 76315c9 · 76315c9
1 parent a944abc
commit 76315c9
Showing 1 changed file with 3 additions and 1 deletion.
diff --git a/README.md b/README.md
@@ -35,5 +35,7 @@ Set the `PYTHONPATH` env variable of the system. Append absolute paths of both t
 
 Three files need to be created for every model, one per training, validation and testing. For R scripts (under src/LSTM-Preprocessing-Scripts), make sure to set the working directory to the project root folder. As an example, *solar_train.txt* file is hardcoded in the scripts. The current source code supports for comma seperated data input, however this can be easily adjustable for other delimiters. 
 
-We assume *solar_train.txt* contain hourly energy consumption observations of multiple households. Each time series consists of 2 years of hourly data, and may present three types of seasonalities; *daily*, *weekly*, and *yearly*. As explained earlier, **SE** and **DS** is used to denote the two different paradigms.  **Baseline** denotes the varaint that does not use any paradigm when training the LSTM-MSNet  
+We assume *solar_train.txt* contain hourly energy consumption observations of multiple households. Each time series consists of 2 years of hourly data, and may present three types of seasonalities; *daily*, *weekly*, and *yearly*. As explained earlier, **SE** and **DS** folders denote the two different paradigms.  Whereas, **Baseline** folder denotes a varaint that does not use any paradigm when training the LSTM-MSNet.
 
+### Generating TFrecords ###
+When training the LSTM-MSNet, we use the tfrecords function provided by the Tensorflow API for a faster execution of our models. The preprocessing scripts used to generate the tfrecords can be found in the `src/LSTM-Models/preprocess_scripts` directory.