Metrics¶
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snap_ml_spark.Metrics.accuracy(dataWithPredictions)¶ - Parameters
dataWithPredictions – binary predictions computed by the LogisticRegression or SupportVectorMachine predict() function
- Returns
accuracy computed based on the binary predictions of a classifier (LogisticRegression, SupportVectorMachines)
- Return type
double
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snap_ml_spark.Metrics.f1score(dataWithPredictions)¶ - Parameters
dataWithPredictions – binary predictions computed by the LogisticRegression or SupportVectorMachine predict() function
- Returns
f1score metric (2*(precision*recall)/(precision+recall)), computed based on the binary predictions of a classifier (LogisticRegression, SupportVectorMachines)
- Return type
double
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snap_ml_spark.Metrics.logisticLoss(dataWithPredictions)¶ - Parameters
dataWithPredictions – probabilities computed by the LogisticRegression predict_proba() function
- Returns
logistic loss computed by the logistic regression predicted probabilities
- Return type
double
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snap_ml_spark.Metrics.meanSquaredError(dataWithPredictions)¶ - Parameters
dataWithPredictions – linear regression predictions, predicted by the RidgeRegression predict() function
- Returns
mean squared error computed based on the provided dataWithPredictions parameter
- Return type
double
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snap_ml_spark.Metrics.precision(dataWithPredictions)¶ - Parameters
dataWithPredictions – binary predictions computed by the LogisticRegression or SupportVectorMachine predict() function
- Returns
precision metric (TP/(TP+FP)), computed based on the binary predictions of a classifier (LogisticRegression, SupportVectorMachines)
- Return type
double
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snap_ml_spark.Metrics.recall(dataWithPredictions)¶ - Parameters
dataWithPredictions – binary predictions computed by the LogisticRegression or SupportVectorMachine predict() function
- Returns
recall metric (TP/(TP+FN)), computed based on the binary predictions of a classifier (LogisticRegression, SupportVectorMachines)
- Return type
double