09.Machine learning04.Time series - sporedata/researchdesigneR GitHub Wiki

1. Use cases: in which situations should I use this method?

• When a time series exist and the primary objective is prediction rather than causal explanation
• Prediction of a clinical event using sensor data from the ICU - see A comprehensive evaluation for the prediction of mortality in intensive care units with LSTM networks: patients with cardiovascular disease which uses MIMIC data

2. Input: what kind of data does the method require?

• Time series data, defined as a collection of repeated measurements over time

3. Algorithm: how does the method work?

Model mechanics

Reporting guidelines

Assessment of Time-Series Machine Learning Methods for Forecasting Hospital Discharge Volume

Data science packages

Suggested companion methods

• RNN

Learning materials

1. Books *
2. Articles
   • Common references for machine learning

4. Output: how do I interpret this method's results?

Mock conclusions or most frequent format for conclusions reached at the end of a typical analysis.

Tables, plots, and their interpretation

5. SporeData-specific

Templates

• Time series

Data science functions

References