false-positive ratio

FPR

The ratio of patients who are disease-free but test positive for an illness, as a result of error, to all patients who do not have the disease.

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Therefore, it is crucially important to interpret the data taking into account the leukocyte number in order to decrease the number of recall patients and the false-positive ratio.

False Positive Diagnosis of Lysosomal Storage Disease Based on Dried Blood Spot Sample; Leucocyte Number of a Challenging Factor

(1) The network energy consumption is sacrificed for higher detection accuracy and lower false-positive ratio. In the existing detection algorithms, the sensor node needs to communicate with its neighbor nodes during fault detection, which will lead to higher energy consumption

The method has high detection accuracy and low false-positive ratio, but it also causes high computational complexity and much energy consumption.

The faulty data will be replaced by the collected normal data at other times for transient faults; therefore, the false-positive ratio can be effectively reduced.

The two indicators are usually adopted to evaluate the effect of fault node identification, namely, detection accuracy and false-positive ratio.

The false-positive ratio (FPR) refers to the ratio between the number of normal nodes which are identified as fault nodes and the total number of normal nodes:

For transient faults, the fault values will be promptly corrected by LEFD to avoid mistaking the normal node as a faulty node, thus reducing false-positive ratio. The simulation results show that LEFD has high detection accuracy, low false-positive ratio, and less energy consumption for various faults.

Fault Detection Modelling and Analysis in a Wireless Sensor Network

* Market-Leading Accuracy: A low false-positive ratio data analytics* based on pre-packaged Windows[R] kernel level endpoint agents focused on insider threat, cyber attack, and data leak (*US patent applied)

Soliton Cyber & Analytics Previews InfoTrace Analyzer, the Next Generation Endpoint-Integrated Behavior Analytics Platform

Three components should be incorporated into an effective and accurate fraud-detection solution--review rate, fraud-detection rate and false-positive ratio.

A false-positive ratio indicates how many applications, on average, will not contain fraud for every confirmed instance of fraud detected at the threshold.

Figure 2 Effective Fraud Solutions Encompass Review Rate, Fraud-Detection Rate and False-Positive Ratio Score Review Rate Fraud-Detection Rate False-Positive Ratio 900 1% 25% 1:1 800 3% 43% 3:1 700 5% 48% 5:1 600 10% 62% 6:1 Note: Every score has a corresponding review rate SOURCE: CORELOGIC Plotting performance can graphically show the "lift" a lender could get from employing the score.

Smarter tools in the fight against fraud: a new generation of fraud-detection tools is helping FHA lenders more effectively fight fraud

This step should reduce false-positive ratio of descriptors matching but causes more false-negative avoiding.

Affine-Invariant Geometric Constraints-Based High Accuracy Simultaneous Localization and Mapping