star classifier using xgboost, web application uses Flask. Classify stars by type, input Temperature, Luminosity, Radius and Absolute Magnitude and returns a numerical type of the star, used by Astronomers.
Work flow
stars_model.py - creates a model from trained data using xgb.Classifier
app.py - runs the application on a web server, routes set the user interface in
this file and loads the precompiled model in .pkl format using Pickle serialization
this file is the model in pkl format, xgbcl_model.pkl.
Flask is the web app python framework
templates/index.html is the html code, user interface, that is called by app.py
model.json is not used but I generate it just in case I choose to use it some day.
data/stars csv.csv is the raw data file that the trained data is taken from.
if you don't want to generate a model on your own, just run app.py in a vitrual
environment in PyCharm, when setting up PyCharm be sure to add Flask
when creating the virtual environment.
see requirements.txt for Python libraries required to run the app