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// make predictions and compare with the ground truth | |
let metrics = partitions.TestSet |> model.Transform |> context.BinaryClassification.Evaluate | |
// report the results | |
printfn "Model metrics:" | |
printfn " Accuracy: %f" metrics.Accuracy | |
printfn " Auc: %f" metrics.AreaUnderRocCurve | |
printfn " Auprc: %f" metrics.AreaUnderPrecisionRecallCurve | |
printfn " F1Score: %f" metrics.F1Score | |
printfn " LogLoss: %f" metrics.LogLoss | |
printfn " LogLossReduction: %f" metrics.LogLossReduction | |
printfn " PositivePrecision: %f" metrics.PositivePrecision | |
printfn " PositiveRecall: %f" metrics.PositiveRecall | |
printfn " NegativePrecision: %f" metrics.NegativePrecision | |
printfn " NegativeRecall: %f" metrics.NegativeRecall | |
// the rest of the code goes here.... |
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