# Timestamp sequence classification

I am trying to classify a series of timestamps using RNN with LSTM. The data consists of timing information extracted from the uplink packets recorded during a website fetch. The dataset contains 100 individual fetch samples of each website in a set of 100 websites, this gives me 10,000 samples.

I would like to teach a neural network to classify sequences of timestamps to which website they belong.

An example sequence would look like:

0.0, 0.25420099, 0.70250899, 0.7434534, 0.8746745, ... 2.54634634


Each of these values represents an offset from the start of the website fetch.

These all differ in lengths and are between ~300 and ~4500 timestamps.

I have tried training the LSTM network in Keras like below:

modelClass = Sequential()

Training data is in the shape of (9000, maximum_sequence_length, 1), however this gave me very bad results. I am new to machine learning and don't fully understand how to find appropriate algorithms for specific tasks. Google searches did not come up with any ways to classify such data.