Questions tagged [false-positive-rate]

In a test for a condition (such as a disease) the false positive rate is the proportion of subjects incorrectly classified as having the condition.

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6 views

Any way to give a predicted value for FDR if you know the ⍺-level + the number of comparisons?

I'm writing a school paper on false positives and the multiplicity problem. I want to show that multiple testing inflates the false discovery rate (FDR) and that FDR increases with the number of ...
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8 views

How to derive false positive and false negative from top-k accuracy?

I am working on the following "equality identification" problem and become quite confused on how to reasonably define false positive and false negative in my case. Problem: Suppose I have a ...
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25 views

False positive rate with multiple dichotomisation

There are reasons this is bad practice, but I want to try and calculate the following - if one takes a distribution (say a normal distribution) and applies $n$ multiple dichotomisations to it and chi ...
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50 views

Aren't all tests sensitive to the prevalence of a disease in the population?

I'm trying to understand the difference between the false-positive rates of two kinds of COVID-19 tests: PCR and antibody. The former indicates if someone is currently sick. The latter indicates if ...
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23 views

One-Class SVM threshold parameter

I have to implement metrics FPR at 95%TPR. In order to do that I have to look for the different decisions of OCSVM dependent on the threshold. If I execute this simple code: ...
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47 views

How can I fix type 1 error for my logistic regression model?

I am testing if the sound pressure levels(rms) of shipping noise affect the presence or absence of the fin whales by acoustic monitoring for 4 months of data from one location. Here my response ...
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23 views

How do you combine confidence intervals for antibody test estimates?

I would like to know how to combine the uncertainty related to the false positive rate of an antibody test with uncertainty due to sampling. As an example, let's use the recent New York State estimate ...
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24 views

How to bias against false positives given estimate and standard deviation?

For 1000 newsletter recipients, I crudely estimate the likelihood (p) of them reading the next email sent as: ...
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18 views

If a false positive rate of α is desired, what is the acceptable range of false positives one would expect from a sample size of n?

For instance, suppose I design a test to have a false positive rate of 5%. I am going to perform this test on what is assumed to be an all negative population. If my sample size was 20, I would expect ...
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24 views

How could one estimate the false positive rate of a deployed fraud detection system?

On a labeled dataset, the FPR of a classifier could easily be measured. However, after a fraud detection system is deployed, we lose the ability to gain a ground truth classification of the positives. ...
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14 views

Procedure to Smooth Noise for Threshold Values

Suppose I am looking at an estimate $\hat\beta$ in a clinical trial data. With $a=.05$, a patient with $\hat\beta>1$ is considered to have some medical condition. A daily example could be a 24-hr ...
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1answer
78 views

Base rate of accuracy after resampling for classification problems

If I had an imbalanced dataset with 10% positive instances and 90% negative ones, the base rate for accuracy before resampling is 90%. But what about I resampled the data such that I have an equal ...
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27 views

Deriving a loss function properly accounting for different error type costs

Consider a classification setting like a medical test: Not finding an existing health issue might be much worse (by a factor of 50) than assuming an issue when there is none. I.e. a setting in which ...
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40 views

What is “positive”?

I'm deeply confused by some concepts. We often hear the term true/false positive/negative. While it is straightforward to tell if the result is true or false, I ...
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2answers
68 views

FPR in Confusion Matrix

I was trying to manually calculate $\text{TPR}$ and $\text{FPR}$ for the given data. But unfortunately I dont have any false positive cases in my dataset and even no true positive cases. So I am ...
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50 views

Oversampling/Undersampling in respect to Train and Test - Isolation Forest

I've got a quite imbalanced data set. 144.496 : 162 -> ratio of 1000:1 I would like to use IsolationForest to detect the 162 anomalys. I've already split the data. However, the iForest doesn't ...
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8 views

Multiple hypothesis correction yields higher FDR on lower number of tests. Why?

I have a DF (df1) with thousands of rows, where each row has a test and associated P, and their corresponding corrected P values (FDR Benjamin-Hochberg). Under ...
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1answer
60 views

False positive/negative rate in ridge and lasso regressions

I have a confusion matrix of true and estimated $\boldsymbol{\beta}$ vectors of lasso and ridge models from a replicate of a simulation study, say. The following tables illustrate the scenario. $$\...
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What would be the True Negatives (TN) and FPR in this case?

I've developed an algorithm that detects shapes in a given image. The input is an image with a triangle, a square and a circle. My algorithm outputs triangle, square, pentagon. If I'm not mistaken, ...
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How to make sense of both high FNR and NPV?

So, even though this is one of the most basic and already explained things about statistics I always seem to find way not to get it. Having this table which shows high Negative Predictive Value (352/...
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74 views

SVM probability output threshold as (1 - FPR)?

I have a binary SVM with probability output (via Platt scaling). I want to set a threshold on the probability outputs since I want to trade off making false positives/negatives. Is it possible to ...
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39 views

How to interpret a False Discovery Rate plot

It is the first time that I am trying to calculate the FDR and I use the fdrtool package in R. I want both, local and tail area graphs and I think the third ...
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13 views

Estimating false accept rates from imposter scores below a threshold

I have a system that compares two items and produces a match score. Scores below a threshold are manually inspected to determine if they match or don't(imposter). Scores above the threshold are ...
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1answer
108 views

Is most published research indeed false?

I have come across (Ioannidis, 2005) which explains several reasons (mainly statistics-related, that's why I post this question here) to justify the claim that most published research is indeed false. ...
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Optimal solution for false positive effect on business strategy

I am facing a challenge to reach an optimal solution. I will try to explain with an example : Suppose I have created an algorithm to predict if a customer will subscribe to bank deposit plan or not. ...
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1answer
98 views

Is it possible to estimate accuracy, precision and recall with the given data?

Background: I talked to my friend today and according to herm(him/her) I can calculate precision, recall and accuracy with the current information. Total instances T: 19,532. Instances belonging to ...
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32 views

Exclude areas of feature space without getting false negatives

I am using a decision tree classifier to split the feature space according to two classes ( A and B). Events of class A are important and I want to classify all of them correct, i.e. no false ...
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Estimating true positive rate with a confidence interval given a classifier + unknown dataset truths

Let's say I've built a binary classifier - one that for instance, can classify whether a particular transaction is fraudulent or not. This classifier outputs a 1 or a 0, with a given degree of ...
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2answers
103 views

Is it the case that β+power=1?

In psychology papers that do prospective power analyses (example), one often notices the convention of assuming β values (false negative rates) of 0.20, and power levels of 0.80. In other words (if I ...
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115 views

What is the integral of the False Positive Rate over the False Positive Rate, compared to the AUC?

In machine learning the Area Under the Receiver Operating Characteristic Curve ($AUC$) can be illustrated in a plot of the True Positive Rate ($TPR$) against the False Positive Rate ($FPR$). Formally, ...
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37 views

How to make really bad results from a machine learning model better by reversing predictions

I trained a classification model on some data with two classes and have really low accuracy. I have a false-positive rate of 86 % for both classes I am trying to predict. I was wondering if I could ...
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118 views

Number of samples required to estimate a desired False Positive Rate

I have an algorithm that for each sample $x_i$ returns an anomaly score $0<s_i<1$. I use cross validation to set a threshold $th$ such that $x_i$ is anomalous if $s_i>th$. During cross ...
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1answer
107 views

How to tell the likelihood of getting a false positive? [closed]

Say we have a test for a disease we are comparing with the gold standard. You are given the prevalence of the disease, which is 1%, and sensitivity, 80%, and specificity, 90% and a total population of ...
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32 views

How are false positives possible? Since shouldn't mathematical methods be “exact”?

That is, it's not possible to have true as false, but isn't that basically what a false positive or a false negative does? That it gives a prediction of a condition existing, when it does not? So how ...
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13k views

FPR (false positive rate) vs FDR (false discovery rate)

The following quote comes from the famous research paper Statistical significance for genome wide studies by Storey & Tibshirani (2003): For example, a false positive rate of 5% means that on ...