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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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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75 views

Does up-sampling lead to lots of false positives in production?

Say we have a dataset with a binary outcome variable that takes the positive case (outcome = 1) roughly 20% of the time. Often, we would modify the training set by ...
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13 views

Sensitivity and specificity with multiple sequential tests

This has been on my mind for a while, and I would appreciate a statistician's view on the matter. Suppose that a given test has sensitivity $a$ and specificity $b$. Now, periodically apply this test ...
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30 views

How do you cope with the risk of false-positives in exploratory analysis?

Let's say that I'm running exploratory analysis on a dataset. For instance, let's say that the dataset consists of several features and two groups and I want to see which features are significantly ...
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16 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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50 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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33 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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151 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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45 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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43 views

Reduce false positive in extremely high imbalance testing set

I have built a CNN model to classify positive and negative in my data, the accuracy is around 85% with FPR is 16%. I know the FPR is high but it gives an acceptable number of FP in training and ...
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7 views

Many identical false negatives in multi-output classification

I used an XGB model to classify 12 categories (I call them classes 1-12). I've found that a particular false positive, 5, is predicted frequently for what should be '2', according to the actuals that ...
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64 views

Interpretation of AUC - ROC curves with a Binary Predictor

I have data like this: ...
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106 views

Equal Error Rate (EER) Metric - Why is lower better?

With the Equal Error Rate (EER) Metric, why is the lower the value the better (more accurate binary classifier system)? Also, when finding the EER on the ROC curve, is it correct in saying the EER is ...
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35 views

Correlation between two non-independent samples (dichotomized data / multiple testing)

I've been looking through text books but unable to find a precise answer to this question, but it seems important so maybe I'm looking in wrong places. Imagine some population with a normal ...
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370 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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138 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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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
22 views

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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23 views

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 ...