Constructing an LSTM Neural Network for Sequence Classification

In the previous chapter, we discussed classifying time series data for multi-variate features. In this chapter, we will create a long short-term memory (LSTM) neural network to classify univariate time series data. Our neural network will learn how to classify a univariate time series. We will have UCI (short for University of California Irvine) synthetic control data on top of which the neural network will be trained. There will be 600 sequences of data, with every sequence separated by a new line to make our job easier. Every sequence will have values recorded at 60 time steps. Since it is a univariate time series, we will only have columns in CSV files for every example recorded. Every sequence is an example recorded. We will split these sequences of data into train/test sets to perform training and evaluation...