Questions tagged [separation]
Separation occurs when some classes of a categorical outcome can be perfectly distinguished by a linear combination of other variables.
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15 views
Preprocessing on unsupervised learning
I am working on a high dimensional problem that evaluates code readability according to specific metrics. The problem is that there is no 'ground truth' so I need to implement clustering (instead of ...
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1answer
34 views
Doubt on d-separation
In the book: Bayesian Networks With Examples in R, the author shows three examples of d-separation:
He cites:
Then, just a few lines below, the author uses the dsep function, which returns FALSE for ...
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47 views
Which theorem in Cover's 1965 paper is actually referred to as Cover's Theorem?
My question is bolded below, some of my reading notes are also shared for those interested.
Cover's Theorem is stated on Wikipedia (and similarly elsewhere) as
A complex pattern-classification ...
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0answers
18 views
likelihood ratio test for logistic regression with a complete separation
Can likelihood ratio test be used for logistic regression in the case of complete separation? I understand that individual parameters can go to infinity so Wald's test is not recommended, but does ...
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1answer
35 views
Clustering Proof of Equation
Greetings! Could anyone enlighten me about the validity of this equation? I'm trying to prove it without success. $K$ is the number of clusters, $C_i$ is the $i$-th cluster, $m_i$ is the number of ...
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1answer
17 views
Relationship between Cohesion and Separation
Hello! May someone explain to me please how to prove the equation depiicted with the red line? Thank you in advance!
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1answer
23 views
Doesn't separation in data affects Random Forest?
I'd like to know if separation in data points given by a certain variable will affect Random Forest in terms of "being a correct built model"? For example, logistic regression is highly vulnerable in ...
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1answer
361 views
Why one result is so wide in this logistic multiple regession
I am doing multiple logistic regression with data with 24 predictor variables and 193 rows.
All predictor variables have values of 0 or 1 and outcome variables (OUTVAR) also has only 2 possibilities. ...
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36 views
Is A ⊥ B | C where one path active but another inactive?
I'm trying to determine if A ⊥ B | C?
I see two paths flowing through elements of C:
(1) B <- C - > A (all variables unobserved, active triple; independence cannot be guaranteed for this path)
(...
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17 views
Cutting dendrogram at certain point
I have a question about cutting dendrogram like that
It shows some hierarchy in the prison
I have to cut it to separate the group.
Is it possible to cut not all dendrograph at the same height like ...
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0answers
52 views
What is the *formal* definition of separation in *binary* logistic regression?
I am trying to understand complete and quasi complete separation in the context of logistic binary regression. However, I have not found a clear source. I know the seminal paper
https://www.jstor....
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99 views
How to show or prove a dataset is not linearly separable
I am looking to be pointed in the right direction. I am learning about kernels and I have a homework assignment to use the dual perceptron algorithm to classify datapoints from a spiral dataset, with ...
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1answer
67 views
Seeking to understand using the Firth correction in Generalized Estimating Equations to deal with quasi-complete separation
In order to deal with complete separation in my data someone suggested that I run penalized GEE (PGEE) by adding a Firth-type penalty term in R.
Although I have read many papers on the Firth ...
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1answer
47 views
Quasi/Complete separation due to huge and infinite values
(R statistics)
My question is regarding this warning. My data contains patients and healthy subjects. Exponential decay is my outcome measure.
I have a example dataset here
I managed to run ...
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1answer
178 views
If logistic regression is a linear classifier why does it fail on linearly separable data?
Logistic regression is a linear model, decision boundary generated is linear.
If the data points are linearly separable, then why does Logistic regression fail? Shouldn't it perform better on data ...
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0answers
33 views
Linear separation in higher dimension [duplicate]
I am having a problem comprehending with the relation of kernel, weight and linear separation.
I have a case where I am given a kernel $k_1$. that has a corresponding mapping $\phi_1$.
And we ...
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0answers
53 views
Logistic Regression: How to Detect Complete AND Quasi-Separation of Data Points
I have written a logistic regression routine using the Newton-Ralphson algorithm in VBA for use in a class that I teach which uses primarily EXCEL. I want the algorithm to test for complete and quasi-...
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0answers
7 views
How to calculate if the given dataset is linearly separable or not using the given discriminant function [duplicate]
I am student and learning SVM with radial basis kernel function and want to solve the question manually by hand. but I am unable to calculate the values to find out whether the dataset is linearly ...
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51 views
How to manually calculate if the given dataset is linearly separable or not using the given discriminant function
I am student and learning SVM with radial basis kernel function and want to solve the question manually by hand. but I am unable to calculate the values to find out whether the dataset is linearly ...
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52 views
R GLMM: How to deal with separation inflating standard errors in negative binomial regression (count data)
I'm comparing counts of individuals between different localities, and between two seasons (seas_wmo with levels dry and ...
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37 views
anomaly detection : check the separability of normal and abnormal data
I'd like to develop an anomaly detection. I have historical data from sensors in the form of time series. The time series can be divided into data of a normal state and data of an abnormal state i.e. ...
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1answer
99 views
Handling quasi-perfect separation in a zero-inflated negative binomial regression in R
I want to run a zero-inflated negative binomial regression in R, but one of my variables exhibits quasi-complete separation and throws errors for both the negative binomial and logistic pieces. I've ...
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1answer
29 views
Dealing with Complete Separation in Logistic Regression when Reporting [duplicate]
I have a question regarding how one would deal with complete separation in logistic regression when reporting the outcome for statistical analysis. For a study, we have group participants into 4 ...
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1answer
4k views
glm.fit: fitted probabilities numerically 0 or 1 occurred however culprit feature is numeric
I've been receiving the warning message in the title and have reviewed posts such as e.g. this one.
I would like to understand how this feature has perfect separation with the target variable, since ...
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0answers
42 views
Dealing with complete separation in Generalized Additive Models
Related to "How to deal with perfect separation in logistic regression?":
I am modelling survival using a binomial mixed model (gamm from ...
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0answers
32 views
Does separation of data matter in Bayesian power calculations with logistic regression models?
I know that, when performing power calculation based on logistic regression model, under the regular frequentist approach, power calculations become unstable if it is based on the model that causes ...
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1answer
43 views
Is there an upper bound on number of logistic regression responses that yield infinite estimates
Suppose a logistic regression problem has N observations of {0, 1} and that there are p parameters. Also assume the design matrix, X, is full rank with p < N. We know that there will be certain ...
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59 views
Logistic regression with separation and nested design in R
Data:
An item can be in the state 0 or 1 (binary). Each year, it starts in the state 0 and then changes to state 1.
I have data of 4 seasons (2010 -2013). Each year I sampled the (same) individuals ...
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2answers
255 views
GLMM for count data using square root link in lme4
I have data from a field survey. The objective of the study is to relate number of seedling (respond variable, count data), landform (exploratory variable, categorical variable with 3 levels) and ...
0
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1answer
134 views
Kullback-Leibler Divergence as the class separation measure
I am trying to use KL divergence as the separation measure between the classes. I have the positive, negative samples for 2 distributions and want to adjust the algorithm parameters to get the best ...
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0answers
13 views
any problems with Firths Logit model (to deal with separation)
I am performing a Logit Model on binary variable SALE, when running on stata some of my explanatory variables were dropped as they were "perfect predictors". after some reading i believe the problem ...
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1answer
148 views
Zero Centering Data
Does zero centering your data make it more linearly separable or does that not affect the separability? I read that by zero-centering the data, it allows algorithms to train faster because small ...
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1answer
277 views
Can I run a logistic regression with a small sample size and perfect convergence?
I'm hoping someone will be able to help me with my question. I have a dataset with 71 records and 4 variables. Three of the four variables are independent, and one is dependent. All four variables are ...
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1answer
77 views
R/Stata Can I include a categorical variable in a Logistic regression when one of its values perfectly predicts one of the outcomes?
Suppose I have the following data
df = data.table('y'= c(1,1,1,1,1,1,1,0,0,0,0), 'x' = c(1,1,1,1,1,1,1,1,1,0,0))
where x = 0 perfectly predicts y = 0. I ...
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1answer
939 views
How to tell which variable is perfectly separated in R [duplicate]
I am running a logistic regression model in R using glm. I received a warning that complete separation occurred. How do I determine which variable is causing this? R doesn't tell you what variable is ...
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1answer
442 views
Why do we sum the cost function in a logistic regression?
I get the intuition behind the loss function for linear regression, which happens to be the MSE function. We have a set of points and we try to fit a line between them so that the line is at a minimum ...
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1answer
702 views
Abnormally high standard error in binary logistic regression
I did a binary logistic regression test on SPSS with a sample size of 24. The study is about the correlation of teenage pregnancy and depressive symptoms. Of the 24, 11 are pregnant teenagers. Of the ...
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1answer
3k views
Issue with complete separation in logistic regression (in R)
I am trying to fit a logistic regression model for business defaults. Apart from the dichotomous variable default, the data set includes some performance ratios.
When estimating the model in R, the ...
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0answers
95 views
When logits are too large in logistic regression, are statistics and p values still interpretable?
I am using glmer() in r to run a mixed logistic regression with 3 categorical (dichotomous) predictors. The outcome measure is whether or not a participant responded correctly to a memory check. This ...
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1answer
2k views
fitted probabilities in logistic regression [closed]
Is the only reason why fitted probabilities of 0 or 1 occur is that some of your predicting variables(x) are perfect linear combinations of the target(y) variable? Is there any other reason?
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1answer
118 views
How do I deal with a perfect fitted model?
I have a data set where one independent variable perfectly predicts the outcome.
Specifically, age will perfectly predict if the user will buy the product.
However, I also have a number of other ...
5
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2answers
394 views
How does perfect separation in logistic regression affect the AUC?
I have been working with perfect separation in logistic regression, and I have been assessing models with the AUC statistic. I was wondering what effect perfect separation has on the AUC. My own ...
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0answers
50 views
How to calculate a perfect separation in a d dimensional space between n class?
Assuming in a d-dimensional space, we have samples from n class.
The best way of separating samples of each class from each other is to have the samples from each class as far as possible from every ...
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1answer
1k views
I think my logistic model is overfitted even with Lasso? R gives me a perfect separation warning message
I have a survey with 25 variables (160 observations for each var). Most are categorical, some are continuous. The variable of interest is categorical (binomial). If I do:
...
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2answers
846 views
How to identify linearly separable datasets
Usually, when I am given a dataset of $d\le 3$, I just plot the data and observe if linearly separable behaviour exists. When the dataset is of high dimensionality, I always follow a simple trick to ...
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0answers
188 views
Does SVM suffer from Quasi-complete separation or perfect separation?
Are SVMs, which use the hinge loss, suffer from Quasi-complete separation or perfect separation? Why or why not? Could you please give mathematical justification?
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2answers
81 views
Clustering Separable but Unequally Sized Clusters
I am trying to cluster the data shown below. The clusters are clearly separable. I've tried k-means and EM clustering (Gaussian mixture), however, both techniques divide the large main cluster into ...
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1answer
1k views
Logistic Regression: p values all '1', yet model fits perfectly [duplicate]
I was trying to help a student and was foxed by this Logistic Regression problem and seek your explanation.
Here's some economic data. All we have to do is create a model to predict whether the ...
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2answers
4k views
Logistic Regression is a Convex Problem but my results show otherwise?
I know that logistic regression is a convex problem. Furthermore, from Lemma 1.17 in these optimization lecture notes, if a function $f : \mathbb{R}^n \rightarrow \mathbb{R}$ is convex, then the ...
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4answers
1k views
Why is it desirable to have linear separability in SVM?
Ref to above image, clearly a circle can separate the two classes(left image). Why then take so much pain to map it to a function to make it linearly separable (right image) ?
Can anyone please ...
