Scoring Functions

GibberishNameScore

Score a given name, username, or email handle for its likelihood of being gibberish. A negative (low) score indicates low likelihood of gibberish. A positive (high) score indicates high likelihood of gibberish. Zero is a good threshold for most use cases.

Syntax:

• GibberishNameScore(text string)

Examples:

GibberishNameScore("Heather Lowenfish") = -1.6666666666666667
GibberishNameScore("cris.johnson1992") = -1.0857142857142856
GibberishNameScore("Uisdfhkj Jasdfyb") = 0.7642857142857142
GibberishNameScore("jsdfhsdfjkhsdf") = 1.6384615384615384

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ModelPredict

Execute a Model on the given inputs and return a struct of output variable names to numeric values. The input and output schema are enforced at compile-time.

Syntax:

• ModelPredict<model_name>(inputs: struct) -> struct

Examples:

ModelPredict<regressor>({x: 1.2, y: -7.5}) = {z: 2.8}

risk_score := ModelPredict<cash_out>({
 amount,
 dollars_in_out_1h,
 dollars_out_by_email,
 emails_per_bank,
 emails_per_device
}).probability_fraud

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