Predicting Star/Galaxy/Quasar using NN
The data consists of 10,000 observations of space taken by the SDSS. Every observation is described by 17 feature columns and 1 class column which identifies it to be either a star, galaxy or quasar. Number of features were reduced to 7 after analyzing the data. The 7 features:
- Ultraviolet (u) better of DeV/Exp magnitude fit
- Green (g) better of DeV/Exp magnitude fit
- Red ( r ) better of DeV/Exp magnitude fit
- Near Infrared (i) better of DeV/Exp magnitude fit
- Infrared (z) better of DeV/Exp magnitude fit
- redshift value
The Thuan-Gunn astronomic magnitude system. u, g, r, i, z represent the response of the 5 bands of the telescope.
The data is then fed to a Sequential Neural Network with 70:30 ratio for training and testing.
Model accuracy: 99% Model loss: 0.035
The trained model is then used for prediction through a Tkinter GUI application. Sample screenshots of the same are attached below:-
