I am a newbie to machine learning and python.
I have a Python code snippet which loads stored ml model and predict with new inputs.
mlModel = pickle.load(open('linear_model4.pickle','rb')) request_body = request.body.decode('utf-8') parsed_request = makePredictionInput(json.loads(request_body)) rb=json.loads(request_body) print(parsed_request) result = mlModel.predict(parsed_request)
It uses 5 inputs for prediction.
Is there a way to get the slopes and intercept from above loaded model sothat i can form the equation as y = intercept + slope1variable1+ slope2variable2+ slope3*variable4+…..
I assume that your model is a linear model given the equation you want to reconstruct.
mlModel.coef_ should be what you want. See this for example.