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Yep, we made our own. I haven't heard of PMML before - quite cool! What we've made is a bit more readable for what we're using it for though, IMO. Looks like this:

    {
        "intercept": 1.0,
    
        "features": {
            "feature_1": {
                "coefficient": 1.0,
                "range": [0.1, 10.0],
                "mean_feature_score": 1.0,
                "imputation_value": 1.0
            },
            {
                ....
            }
        }
    }



Is this open source? We were looking for something like this.


Sadly not. I'd be totally up for open sourcing if there's clear demand. If you can find it, send me an email at angus@{company_I_work_at}.com

Note that it's very tied down to our use case right now: only compatible with Logistic Regression, and currently it assumes fixed hyperparameters (will change this in future though), assumes a production pipeline of min-max scaling, imputation, then classification.




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