Questions tagged [threshold]

Used (1) for discrete classification (if an instance's predicted probability exceeds a threshold, classify as TRUE, otherwise FALSE), or (2) for discretizing/binning continuous data. *If you are tempted to use this tag, PLEASE read the tag wiki!*

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59
votes
4answers
39k views

Reduce Classification Probability Threshold

I have a question regarding classification in general. Let $f$ be a classifier, which outputs a set of probabilities given some data D. Normally, one would say: well, if $P(c|D) > 0.5$, we will ...
9
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1answer
154 views

Decision rule as a hyper-parameter in LASSO

I have a question that is related to the following: Is decision threshold a hyperparameter in logistic regression? but would like some clarification. The general consensus is that the decision rule ...
14
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5answers
2k views

Philosophical question on logistic regression: why isn't the optimal threshold value trained?

Usually in logistic regression, we fit a model and get some predictions on the training set. We then cross-validate on those training predictions (something like here) and decide the optimal threshold ...
2
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1answer
205 views

Investigate correlation conditional on a threshold

I have 3 variables in my data set. (i) My gut feel says variable1 and variable2 are correlated, only when variable3 >= threshold3. What is the technique I can use to see if this holds true, to ...
15
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1answer
18k views

What is F1 Optimal Threshold? How to calculate it?

I've used h2o.glm() function in R which gives a contingency table in the result along with other statistics. The contingency table is headed "Cross Tab based on F1 Optimal Threshold" Wikipedia ...
2
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2answers
15k views

How to select a threshold for logistic regression in case of imbalance in class distribution [duplicate]

Consider the model fit2 <- glm(y~x+z,data=records,family=binomial) I have about 42000 records, of which close to 38000 belong to class y=0 and the remaining 4000 belong to class y=1. In order for ...
0
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1answer
43 views

Set proper threshold for binary prediction in ElasticNet

I have long been struggling with setting a valid threshold t for predicting my binary logistic model and hereafter evaluate how well it performs (see code below). I ...
11
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3answers
12k views

Why is the bias term in SVM estimated separately, instead of an extra dimension in the feature vector?

The optimal hyperplane in SVM is defined as: $$\mathbf w \cdot \mathbf x+b=0,$$ where $b$ represents threshold. If we have some mapping $\mathbf \phi$ which maps input space to some space $Z$, we ...
5
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2answers
17k views

Threshold in precision/recall curve

While I was reading Torgo's Data Mining with R, I found that the description of precision/recall curve was different compared with other approaches. Usually, these curves are based on a threshold that ...
3
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1answer
2k views

Time series: probability to exceed a certain threshold

I'm a beginner and I have a generic time series and I want to know the probability that it reach a certain threshold in the future. For example, the time series is day average temperature and I want ...
2
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0answers
7k views

Distance threshold for clustering

Usually online clustering methods (based on kmeans or not) define a distance threshold value. If a new data-point $x$ is far enough from the nearest center $c$ (i.e. the distance from $x$ to $c$ is ...
0
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1answer
789 views

Logistic regression - cutoff

If you are running logistic regression on data, and the prior probability of the event is 50%, and there is no preference for sensitivity or specificity... When would you still want to use a cutoff? ...
2
votes
1answer
315 views

Is there a formal reason for identifying and using “knee/elbow points”?

I am trying to understand the reasoning behind identifying knee/elbow points as suitable thresholds. From what my own intuition tells me, the use of a knee/elbow point is akin to determining an ...
1
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1answer
88 views

Are 0-1 thresholds always equivalent to x-axis thresholds?

I am trying to understand a theoretical issue about the nature of thresholds in binary classification. In medical research, cut-off points are usually chosen along the possible values of the ...
1
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1answer
680 views

Multilayer perceptron for binary classification: threshold learning

In a basic contest, the MLP loss function (cross entropy) uses as value for the label ŷ: +1 if the net output is greater or equal to 0.5 -1 otherwise Where the net output is a value in [0,1] ...
0
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0answers
73 views

How to create a binary threshold from Cosine distance between 1-D arrays?

I have a graph of the Cosine distance between the question and the sentence most similar to it when there is an answer and when there is none. I want to establish a threshold on the abscissa axis ...