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False Positive Rate False Positive Rate
"... The performance of each score function is evaluated by the ROC curve of sensitivity and false positive rate. For each score function and a threshold t, domain pairs with score at least t are predicted as interacting. The predicted domain interactions are compared with the domain interaction in iPfam ..."
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The performance of each score function is evaluated by the ROC curve of sensitivity and false positive rate. For each score function and a threshold t, domain pairs with score at least t are predicted as interacting. The predicted domain interactions are compared with the domain interaction in i
On the false-positive rate of Bloom filters
- REPORT, SCHOOL OF COMP. SCI., CARLETON UNIV., 2007.HTTP://CG.SCS.CARLETON.CA/ ¼ MORIN/PUBLICATIONS/DS/ BLOOM-SUBMITTED.PDF
, 2007
"... Abstract. Bloom filters are a randomized data structure for membership queries dating back to 1970. Bloom filters sometimes give erroneous answers to queries, called false positives. Bloom analyzed the probability of such erroneous answers, called the false-positive rate, and Bloom's analysis h ..."
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Cited by 28 (0 self)
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Abstract. Bloom filters are a randomized data structure for membership queries dating back to 1970. Bloom filters sometimes give erroneous answers to queries, called false positives. Bloom analyzed the probability of such erroneous answers, called the false-positive rate, and Bloom's analysis
Learning at Low False Positive Rates
- CEAS
, 2006
"... Most spam filters are configured for use at a very low falsepositive rate. Typically, the filters are trained with techniques that optimize accuracy or entropy, rather than performance in this configuration. We describe two different techniques for optimizing for the low false-positive region. One m ..."
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Cited by 16 (2 self)
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Most spam filters are configured for use at a very low falsepositive rate. Typically, the filters are trained with techniques that optimize accuracy or entropy, rather than performance in this configuration. We describe two different techniques for optimizing for the low false-positive region. One
Data Pre-processing for Reducing False Positive Rate
- in Intrusion Detection, International Journal of Computer Applications (0975 – 8887) Volume 57– No.5
, 2012
"... Intrusion detection plays vital role in computer network security since long. Experience has shown that most IDS struggle for curbing false positive rate. As part of our proposed model with the objective of reducing false positive rate here we have focused on preprocessing functionality. The main ob ..."
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Cited by 1 (0 self)
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Intrusion detection plays vital role in computer network security since long. Experience has shown that most IDS struggle for curbing false positive rate. As part of our proposed model with the objective of reducing false positive rate here we have focused on preprocessing functionality. The main
system with a low false positive rate
, 2007
"... The performance of current EEG-based self-paced brain–computer interface (SBCI) systems is not suitable for most practical applications. In this paper, an improved SBCI that uses features extracted from three neurological phenomena (movement-related potentials, changes in the power of Mu rhythms and ..."
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and changes in the power of Beta rhythms) to detect an intentional control command in noisy EEG signals is proposed. The proposed system achieves a high true positive (TP) to false positive (FP) ratio. To extract features for each neurological phenomenon in every EEG signal, a method that consists of a
potential pitfall of high false positive rate
"... imaging for diagnosing acute cholecystitis: the ..."
Approximate False Positive Rate Control in Selection Frequency for Random Forest
"... Random Forest has become one of the most popular tools for feature selection. Its ability to deal with high-dimensional data makes this algorithm especially useful for studies in neuroimaging and bioin-formatics. Despite its popularity and wide use, feature selection in Random Forest still lacks a c ..."
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crucial ingredient: false positive rate control. To date there is no efficient, principled and computationally light-weight solution to this shortcoming. As a result, researchers using Random Forest for feature se-lection have to resort to using heuristically set thresholds on feature rankings
Screening mammograms by community radiologists: Variability in false-positive rates
- Journal of the National Cancer Institute
, 2002
"... Background: Previous studies have shown that the agree-ment among radiologists interpreting a test set of mammo-grams is relatively low. However, data available from real-world settings are sparse. We studied mammographic examination interpretations by radiologists practicing in a community setting ..."
Abstract
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Cited by 11 (0 self)
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and evaluated whether the variability in false-positive rates could be explained by patient, radiologist, and/or testing characteristics. Methods: We used medical records on randomly selected women aged 40–69 years who had had at least one screening mammographic examination in a community setting between
The False-positive Rate of Thoracic Outlet Syndrome Shoulder Maneuvers in Healthy Subjects
"... Objective: To estimate the incidence of false-positive findings of thoracic outlet syndrome (TOS) shoulder maneuvers, Adson's test (AT), costoclavicular maneuver (CCM). elevated arm stress test (EAST), and supraclavicular pressure (SCP) in healthy subjects. Methods: A cross-sectional, observat ..."
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%; and paresthesias in 11%, 15%, 36%, and 15% of cases, respectively. The following outcomes had reasonable false-positive rates (upper 95% confidence limit): pain with the AT (7%). CCM (7%), SCP (lo%), or any 2 TOS shoulder maneuvers (10%); discontinuing the EAST because of symptoms (16%); or any symptom with 3 (13
Results 1 - 10
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55,926