autonomous019 / star_classifier_flask

ML Classifier using xgBoost and Flask, gives star type by adding new data to trained set

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star_classifier_flask

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

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ML Classifier using xgBoost and Flask, gives star type by adding new data to trained set


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