Questions tagged [binary-data]

A binary variable takes one of two values, typically coded as "0" and "1".

Filter by
Sorted by
Tagged with
0
votes
0answers
19 views

Binary Logistic Regression using SPSS for Non-Dichotomous Independent Variables

Im using SPSS for binary logistic regression but one of my independent variables is non-dichotomous and categorical (genotype - there are 5 gene combinations possible). I am trying to see if a ...
2
votes
1answer
124 views

Should I use predict_proba or predict when computing metrics

I need to compute some metrics for binary classification. I see that many times some people use the probability: ...
2
votes
1answer
352 views

Why are means not relevant to binary variables?

Trying to learn Basic Statistics from the Coursera. At the time 29 second, the video says: Means are not relevant with such a binary variable. Why?
0
votes
0answers
15 views

nested logistic regression model [duplicate]

I had a dataset that consists of 20000 chess matches. In this dataset, there are columns and variables- such as the players' ratings- that might have an impact on binary data, a white player is more ...
13
votes
3answers
1k views

How would I bias my binary classifier to prefer false positive errors over false negatives?

I've put together a binary classifier using Keras' Sequential model. Of its errors, it predicts with false negatives more frequently than false positives. This tool is for medical application, where I'...
0
votes
1answer
38 views

which hypothesis testing model to use for binary data

I have a dataset that contains 20000 chess matches. I hypothesize that 'is white more advantageous?', and there are features like standard match time of each match and the number of turns in each ...
0
votes
0answers
11 views

Which models can be used to explain data with oscillating binary variables?

The title may be confusing so let me show for demonstration purpose a one-dimensional feature vector x = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] and the corresponding ...
0
votes
0answers
33 views

Leave one out cross-validation performance

I am using LOO CV with XGBoost for binary classification of a set of biomedical data and getting very different results in terms of the AUC value compared with a 10-fold CV on the same dataset. For ...
3
votes
1answer
92 views

Granger Causality Analog for Binary Time Series

Is there a generalized form of granger causality that can be applied to two binary time series? By binary time series I mean an ordered series of values that take values 0 or 1.
0
votes
0answers
5 views

Binary Repeated Measures with One Group

I have a set of experiment data that has one group of participants who answered questions under different experimental conditions (about 5 questions per experimental condition combination). The ...
2
votes
1answer
113 views

Categorical independent variable and binary dependent variable

Which test can I use for analyzing the effect of a categorical independent variable, such as preoperative ASA score (1/2/3/4), on a binary dependent variable, such as postoperative complication (yes/...
0
votes
0answers
57 views

How to tune hyperparameter with imbalanced data

I am doing an hyperparameter tuning through GridSearchCV for a binary classification. ...
1
vote
1answer
134 views

No Activation Function on Output Layer for Binary Classification

In this pytorch example, the output layer does not have an activation function even though the neural network is being used for a binary classification task (i.e. ground truth values are either 0 = ...
2
votes
1answer
49 views

How to analyse binary responses for various factors, including interactions: chi square, mixed models, logistic regression, or ANOVA on percentages?

I run an experiment where subject had to recognize an emotion from various musical stimuli (which were composed with a certain emotional intent). There were 4 levels of emotional_intent, subjects ...
1
vote
0answers
22 views

Which are some formal approaches for predicting multiple binary time series?

I have 10000 roughly similar individuals. For each individual I've got a response (binary time series), 200 explanatory features (also time series), and 10 static features that represent ...
1
vote
0answers
88 views

Binary classification, imbalanced dataset optimization: AUC vs logloss

I'm running optimization on an imbalanced dataset and need to define my optimization metric. I'm working on disease detection so maximizing AUC might not be the best solution, as the certainty of the ...
1
vote
1answer
86 views

Post-hoc Power analysis to question a non-significant difference?

so we did this study about surgical success-rates in two groups (n=84 respectively). The outcome is binary (success vs. failure). A priori we expected them not to differ and, indeed, there was no ...
0
votes
1answer
61 views

Unbalanced dataset classification problem

I have a binary classification problem and I'm working with an unbalanced dataset. The count for each class in the training set looks like: ...
0
votes
2answers
35 views

Calculate probability of outcome of a medical procedure

I have data on medical procedures completed at hospitals in major U.S hospitals. Each medical procedure is assigned a code, for example: Kidney Transplant is X6571. I define the success criteria and ...
0
votes
0answers
37 views

Which Kappa to use in R to calculate agreement for binomial data (0 or 1) between two raters?

I have a dataset in which two raters (Human raters VS. ML model) assign "0" to pseudowords if they consider it as being masculine or "1" if they think they are feminine. So, it is ...
0
votes
1answer
86 views

How to analyze contingency table for multiple responses in SPSS or JASP?

I have two categorical (binary) variables: Gender (female vs. male) and 3 subject exams (English, Math, Science: Pass or fail). Everyone took all the subject exams (repeated measures). How can I ...
1
vote
0answers
24 views

What is an appropriate model for K continuous parameters on [0, 1]?

Question Summary What kind of model is appropriate for estimating K parameters on [0, 1]? In particular, what kind of joint posterior should a model put on K parameters with support [0, 1]^K? ...
0
votes
0answers
12 views

Help in calculating diagonal covariance matrix for generative model for binary classification

I am given this data. I want to fit a generative model $\cal{N}(\mu_0, \sigma_0^2 I_2)$, $\cal{N}(\mu_1, \sigma_1^2 I_2)$ for the $0$ and $1$ classes respectively using $\textbf{MLE}$ and plot ...
1
vote
0answers
65 views

Low birth weight in infants: A binary data example

Using the birthwt data from R's MASS package, I'm trying to solve the problem as posed in Modern Applied Statistics with S-PLUS ...
0
votes
0answers
189 views

Is it possible to use Transformer model for binary classification of unbalanced panel data?

So I have unbalanced panel data, i.e. multivariate time series with different lengths for each individual and a binary label at each time point. I was thinking to use some deep learning approach and ...
1
vote
0answers
6 views

Bounding error of percentage estimation on binary data for small populations

Let's say you have a set $X$ with $N$ elements belonging to one of two categories. So, $x \in X$ can be of type A or B (these categories are mutually exclusive). The elements, however, are not ...
0
votes
0answers
17 views

Intervention Analysis with binary time series

I need to do a intervention analysis to see if a marketing campaign affected conversion rate. I would normally would use Causal Impact package to train a time series and then forecast it on the post ...
0
votes
0answers
14 views

Fuzzy Augmentation and Logistic Regression: Percentage Dependent variable

Let's say the dependent variable is 1 = Good and 0 = Bad. Using Fuzzy Augmentation, I obtained an observation with a dependent variable of 0.6. Is using Logistic regression with more than "2"...
3
votes
0answers
21 views

How to find the [marginal] effect of X on Y when Y is binary and very rare. Can I make groups of similar X and model counts of Y instead?

tl;dr How to model the causal impact of X on binary Y when Y is very rare. Can I make groups and model count instead? Background/What I tried I want to know what the effect of the number of "...
0
votes
1answer
40 views

What is the standard way of plotting confusion matrix for binary classification?

I don’t understand the confusion with the matrix for Binary Classification. I was referring different documents for this, meaning sometime I see that the confusion matrix is plotted Actual Class Vs ...
1
vote
1answer
210 views

Can we treat gender as ordinal variable?

I know this question is stupid, but it is really make me confused. If we have the gender variable, and then encode it as 0 (female) and 1 (male). Most people would say we should treat gender as ...
7
votes
3answers
441 views

Plotting binary vs. binary to identify relationship

What would be the best plot for binary vs. binary to identify the relationship between two variables? Say I have a dataset like this. ...
0
votes
0answers
14 views

In probit model, why demeaning the data of a regressor lead to no change in numerical values for estimated coefficients except for the constant?

Supppose I have data $\{Y_i,X_{1i},X_{2i}\}_{i=1}^{n}$ generated by model $Y_i=\mathbf{1}(a+b_1X_{1i}+b_2X_{2i}>e_i)$, where $\mathbf{1}(\cdot)$ is the indicator function. I try to estimate this ...
0
votes
1answer
28 views

Is it possible for a binary classifier to have lower accuracy, macrof1 and binaryf1 but higher ROC AUC? [duplicate]

I've got the results of two classifiers based on 5 different splits of training and testing sets. Their mean and std of the results are as follow: Method-------Accuracy -- MacroF1 -- BinaryF1---- ROC ...
1
vote
0answers
23 views

Modeling rare event

I'm working with a dataset with roughly 14K records, and am trying to predict a binary variable (death). While the total dataset size is sufficient, the patients with deaths I'm trying to predict make ...
0
votes
0answers
25 views

CUSUM analysis for binary variables

I have a doubt about implementing CUSUM analysis for binary variables (example: failure/success). Is this a good method to detect a change over time for binary variables?
0
votes
0answers
5 views

how to independetly asses trial number and sample size estimation error variance in logistic regression

I have a doubt about the analysis of binary data, mainly from experimental psychology tasks in which each trial can have a correct or incorrect response, and each subject j performs n trials. Often, ...
0
votes
0answers
14 views

How can I improve inspection of the performance of my deep image binary classifier when I have additional data for my classes?

I have some image and also some other attributes (metadata) for each image describing the conditions. My trained classifier's input is only images, and I want to debug the weak points of it using the ...
1
vote
1answer
174 views

How to estimate the minimum required sample size to reach a certain significance level for a binomial test?

I'm about to conduct an experiment where I will measure a binary variable. I will test two different settings of a machine and then I want check whether these two settings yield different proportions ...
0
votes
2answers
29 views

What statistical test should I use to check the difference in a binary variable?

I want to test two different settings of some process which produces an output value based on a parametrized probability distribution (the exact distributions are unknown to me, but they are ...
0
votes
1answer
16 views

Comparing multiple proportions of one sample

Let's say I am testing 5 products (e.g. 5 brands of apple juice) and I have 200 respondents. That is, my data consists of 200 rows and 5 columns (variables/products). For each of the 5 products, each ...
1
vote
0answers
27 views

Does the coefficient from regressing a binary variable on a binary outcome only show the effect of when that binary variable is true?

I have a conditional fixed effects logistic regression of parental health shocks (0 if no shock, 1 if health shock) and clinically problematic child development (0 if no development problems in the ...
0
votes
0answers
18 views

How to use maximum likelihood to estimate the prior probabilities?

Suppose we have 2 classes k = 1, 2 and the class conditioned densities are given by Gaussian distributions with a shared covariance matrix. Suppose we are given a training data set {(xi; yi)} where i =...
2
votes
0answers
25 views

How to decide which features are important in this binary classification task?

Consider a binary classification problem, where the dataset is highly imbalanced, with only around 20% positive labels and 80% negative labels. Feature A has higher AuROC when considering all the data,...
0
votes
0answers
53 views

A question about normalization in probit model (binary response model with normal error)

Suppose I have data on $\{Y_i,X_{1i},X_{2i}\}_{i=1}^{N}$ and the data generating process is $Y_i=\mathbf{1}(\beta_1X_{1i}+\beta_2X_{2i}>e_i)$, where $e_i\sim N(0,\sigma^2)$. Usually, we do a ...
-1
votes
1answer
428 views

maximum likelihood and OLS - true or false [closed]

I was wondering about these three accusations, whether they are true or false and why is that? The maximum likelihood estimation maximizes the sum of squared residuals. Maximum likelihood estimation ...
0
votes
1answer
252 views

How to estimate the optimal cutpoint for a binary outcome in python?

I have a dataset of diabetic patients which has been used to train an xgboost model in several outcomes such as stroke, amputation, and more. Originally we used the continuous numeric variables as-is, ...
0
votes
0answers
45 views

Is it possible to create a binary classifier from bayesian network?

I have a labeled data set consisting of longitudinal data and I would like to train a dynamic bayesian network. The output should be probability of the observation being 1 in a selected step given the ...
0
votes
0answers
23 views

Generate binary classification data in python?

Is there a simple way to generate binary classification data in python? I'd like to specify $X$ input parameter, $[x_1,...,x_n]$, and generate a dataset such that the (overall) McFadden's pseudo $R^2$ ...
0
votes
0answers
75 views

Calibration measure for classification with linear slope

I would like to know if there is a measure for calibration, in binary classification case, that is global, and not only a visual one, like reliability/calibration plot/curve. In particular, in another ...

1 2
3
4 5
24