1. Introduction
2. Method
2.1. Linear regression algorithm
2.2. Feature selection
2.3. Feature computation
2.4. Missing features
3. Training set
3.1. Cleaning
3.2. Final training set
4. Performance of the method
4.1. Overall redshift precision
4.2. Impact of the photometric errors
4.3. Impact of the position in the colour-magnitude space
4.4. Impact of missing features
5. Comparison with other photometric features
5.1. Aperture colours vs Kron colours
5.2. PS1 features vs SDSS features
6. Practical guidelines for using the method
7. Summary