AggregatedVariablesImpactExplanation
import type { AggregatedVariablesImpactExplanation } from "https://aws-api.deno.dev/v0.4/services/frauddetector.ts?docs=full";The details of the impact of aggregated variables on the prediction score.
Account Takeover Insights (ATI) model uses the login data you provide to continuously calculate a set of variables (aggregated variables) based on historical events.
For example, the model might calculate the number of times an user has logged in using the same IP address.
In this case, event variables used to derive the aggregated variables are IP address and user.
interface AggregatedVariablesImpactExplanation {
eventVariableNames?: string[] | null;
logOddsImpact?: number | null;
relativeImpact?: string | null;
}§Properties
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eventVariableNames?: string[] | null
[src]The names of all the event variables that were used to derive the aggregated variables.
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logOddsImpact?: number | null
[src]The raw, uninterpreted value represented as log-odds of the fraud. These values are usually between -10 to +10, but range from -infinity to +infinity.
- A positive value indicates that the variables drove the risk score up.
- A negative value indicates that the variables drove the risk score down.