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Questions tagged [binary-data]

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

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Highly unbalanced data set .Minority Class 1 %

I want to optimize precision and recall i.e f-score but I want to keep high precision . What are the possible ways of doing binary classification on such imbalanced data set [Minority class 1 %]. I'...
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22 views

Can a linear and logit model have the same shape?

While I was working on an exercise based this book, I discovered something interesting. When I fit a logit and simple linear probability model on the data (see code below), the predictions are almost ...
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18 views

Model Performance using Precision as evaluation metric

I am dealing with an imbalanced class with the following distribution : (Total dataset size : 10763 X 20) 0 : 91% 1 : 9% To build model on this dataset having class imbalance, I have compared ...
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15 views

Jaccard Index for Binary Data in R using dist function

I have a presence/absence table of 0s and 1s and I would like to cluster this data. I want to create a pairwise matrix using R's dist function which has a binary ...
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1answer
21 views

Compare results: dependent variable continuous vs binary

I'm using an R package to run interaction between genes using genetic markers (SNPs - single nucleotide polymorphisms). The package allows functions for phenotype (dependent variable) continuous and ...
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17 views

PCA on numerical, ordinal and dichotomous data [duplicate]

I'm new to PCA and basically all the textbook exercises I've done use numerical variables However, I came across a question on PCA with ordinal categorical data (2 variables which represent answers ...
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8 views

which statistical test to use (5 binary IVs and 1 ratio DV)

I'm conducting a study where I have data that include 5 Binary independent variables (0 or 1) and a ratio dependent variable (performance 0.0 to 1.0). I want to check the effect of the IVs on the DV ...
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17 views

How can you meta-analyse continuous and binary repeated measures outcome data?

Context: the random effects meta-analysis is of studies that measure visits to the doctor (visits), as a continuous variable (by reporting mean visits and respective standard deviations) or as a ...
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Evaluating individual Open-Rates in Email Marketing

at my company, we use email marketing to engage with our users, and I want to evaluate their performance. The standard metrics for that would be Open Rate, Click Rate, and Click-to-Open Rate. Take ...
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Comparison effects of regressors for several dependent variables

I want to study the effect of two explanatory variables $X$ and $Z$ on four different outcomes (which are binary variables, i.e. equal 1 if satisfied and 0 if disatisfied): $Y_1$, $Y_2$, $Y_3$ and $...
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1answer
45 views

Fitting the Poisson distribution to binary data

I'm studying several time series. The variables of interests are dummy variables which take value 1 when a certain event happened, 0 otherwise. I want to find the best distribution to describe these ...
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21 views

How can i calculate Covariance between numeric attributes and Binary attributes?

I want to calculate covariance between binary attribute and numeric attribute For example: if x is numeric attribute, y is binary attribute. Then how can i calculate cov(x,y)?
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1answer
59 views

multiple logistic regressions with binary predictors vs single logistic regression with categorical predictors

I would like to know which is statistically more advisable and what are the advantages and disadvantages of each approach. My data frame data has ...
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14 views

Statistical test to measure significant difference between 4 binary classifiers?

I have four versions of a neural network hardware. I am testing the hardwares to classify a single binary input into a binary output. The ANN hardwares are trained using a very simple relation, the ...
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1answer
22 views

Comparison of the mean of a binary variable from two independent sets

I have two sets of data, one is akin to high performing companies, and the other contains low performing companies. I want to compare the mean of a binary value. For instance, "CEO has a bachelor ...
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37 views

How to get the right correlation matrix for correlated binary data [closed]

I am trying to generate correlated binary data in high dimensional in R using bindata lib given marginal probabilites and correlation matrix, but it give me always error ...
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31 views

Frequency analysis of categorical/binary data

I want to do frequency analysis with a data set of consecutive binary values, such as "Rainy - Sunny - Rainy - Rainy - Rainy - Sunny - ...". Using this data, I want to extract the frequency (= the ...
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2answers
26 views

All positive Beta exponents in a binomial logistic regression

I'm running a regression in which the predictor is a categorical measure of living arrangement (1=two parent household, 2 = single parent, etc). There are 8 total categories in this variable. I'm ...
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1answer
56 views

What is the baseline of the F1 score for a binary classifier?

I know how to calculate the baseline for the accuracy of a binary classification problem: I simply always predict the majority class, e.g. if there is 94% True values and 6% False values, my baseline ...
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27 views

Approximating Binary Target Vectors using Machine-Learned Boolean Functions of Logical Statements

I was wondering if there exist any ML algorithms for finding the "best possible" Boolean function whose output will approximate a binary target vector. My data consist of roughly 100k observations (...
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1answer
33 views

Is it methodologically correct to, in some specific situations, merge related binary variables into one continuous?

I have 10 yes/no binary variables regarding different types of economic risks associated with running a startup. I have a database of around 100 different startup companies evaluated on each of those ...
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19 views

Impact of C on geometric margin in linear SVM

Will the geometric margin always decrease if we increase $C$ in a linear SVM? When data is linearly separable, that makes sense but I can't really see it when we have nonlinearly separable data.
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20 views

Why isn't accuracy of binary classification model improving? [duplicate]

I have a data set with a binary response variable, about 30,000 observations of 8 features, some are continuous and some are categorical. This is an imbalanced data set, the ratio of negatives to ...
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1answer
39 views

Correcting sample selection bias of binary classifiers

In fraud investigation the number of detected fraud cases can be very small when compared to the total number of cases. This would also apply to rare desease detected in a very small number of people ...
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1answer
41 views

Linear Regression For Binary Independent Variables - Interpretation

I have a dataset where I want to predict inflow (people joining a platform) but my all independent variables are binary categorical (0,1). Whereas I want to predict continuous variable (inflow -- ...
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17 views

Binary survey confidence

A simple one question Yes/No survey was sent to about 250 people from a population of 481. 135 responses received showed about 80% “Yes” and 20% “No”. How do I calculate my 95% and 99% confidence ...
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13 views

Univariate Feature Selection KBest Test Score Function with Binary Target

What is/are good score functions for univariate feature selection tests when the target variable is binary? Are any of the available scoring functions bad, aside for the regression functions of course....
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Predicting Daily Binary Variable with Mostly Monthly Variables

I have a binary classification task with a dataset composed of a time series of independent events. As part of my data augmentation efforts, I have found a lot of economic indicators that however ...
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1answer
57 views

Linear mixed model for placement of nuclear stress in 10-word turns

I'm trying to model the placement of nuclear stress in 10-word turns in a linear mixed model but am very new to mixed modeling. The model includes these variables: ...
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12 views

Repeated measures to predict binary outcome

I would like to predict outcome of an event based on repeated measures. The problem is the following one: I have 100 patients with measures of a certain feature at different times, but all the ...
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1answer
24 views

Correct Type of Statistical/Machine Learning Analysis For Inflow

I want to predict the number of people joining (inflow e.g. 4000, 5000, 6000 etc) online subscription. The dependent variable is ‘inflow in the first 4 weeks for a certain content title’ as this is ...
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29 views

How do I include new features that did not exist before into an existing model?

I have a binary classification model predicting sports result with features covering 10 years worth of matches. However, how would I feed new tracking data that is only limited to the last 3 years. ...
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38 views

How should I interpret the coefficient in the output of this Logistic Regression? [duplicate]

This is a binary model that my colleagues and I developed that regards a connection between the satisfaction with air (dependent variable) and overall satisfaction with public transport (covariate). I ...
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1answer
61 views

How to interpret the results from a binary model done in R? [duplicate]

This is a binary model that my colleagues and I developed that regards a connection between the distance (dependent variable) and overall satisfaction with public transport (covariate). I don't know ...
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24 views

Model subgroup- and covariate-specific effects for binary outcome over time

I am currently planning an analysis, in which I try to separate the change in the level of a binary outcome into a subgroup- and a covariate-related effect. Let's say there are three kind of ...
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39 views

Grouped and ungrouped binary data: different results in R and Stata

I am working with grouped binary data in order to reduce my data from many individual observations (2.2m) to far fewer covariate patterns (approx 12.5k). Doing so should produce the same results in a ...
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1answer
43 views

Binary classification and target-label proportion

Suppose that we have a binary classification problem with a vector y = [1 1 0 1 0 0 1 ... 0] having the proportion: ...
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1answer
34 views

Logistic Regression predict_proba keeps on increasing when I increase the value of the most predictive feature

I am applying logistic regression to predict a target variable ( success or no-success).I added some new features, tested my AUC.My AUC initially was 0.6, and it increased to 0.7 when I added ...
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2answers
85 views

When is logit function preferred over sigmoid?

I found out that logit and sigmoid functions are inverse of one another, and are used in binary classification, but is there a preference of one over another in any circumstances, or can they be used ...
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1answer
36 views

How to model a binary vector by the Beta-Bernoulli distribution in R or Python?

I have a set of data $x=(x_1,x_2,x_3,...)$;e.g:$x=(0.1,0.003,0.78,...)$ which follows a beta distribution. Since $x_i$ in my data $x :x_i ~ Bernoulli(p)$, where $p$ is the prior of average $x$ and ...
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1answer
104 views

Bernoulli Naive Bayes with Unbalanced Classes of Binary Features

I'm using a multivariate Bernoulli model with a Naive Bayes classifier on binary features. It's giving a lot of very low estimates of the probability that each instance is correctly classified. I ...
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1answer
38 views

What is the probability/likelihood of a sample being drawn from a probability distribution over binary values

Suppose we have a known discrete probability distribution $X$ over $\{0,1\}^k$. Given a sequence of binary values $e = (e_1, ..., e_n)\text{, where } e_i\in \{0,1\}^k$, what is the probability (or the ...
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1answer
84 views

Using binary factors as predictor variables in piecewiseSEM in R

I am looking for help with the use of categorical binary predictor variables in the piecewiseSEM package in R. I am inspecting the effect of two categorical variables on one continuous response ...
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1answer
31 views

Interpretation of quantitative variable in regressions with and without dummy variables

I was provided with results from two regressions: (1) log(annual_salary) = B1*yrs_experience + B2*PhD + B3*Masters + B4*Bachelors + e (2) log(annual_salary) = B1*yrs_experience + e where '...
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45 views

One-tailed test for comparing paired dichotomous responses

Given reference samples $R_i$, I have two dichotomous responses $X_i$ and $Y_i$ I wish to compare. Each dichotomous response (relevant vs. irrelevant to the reference $R_i$) is generated by an ...
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2answers
42 views

How can we change gender preference into dichotomous variable when the categories are male, female or any in order to conduct logistics regression?

How can we change gender into dichotomous variable when the categories are male, female or any in order to conduct logistics regression? My research is about gender preferences at the time of birth, ...
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1answer
45 views

How to deal with missingness of dependent variable in unbalanced probit model

I am trying to estimate a probit model on the probability of suicide over the next year in a population. Unfortunately for this research, suicide rates are very very low so the probability of suicide ...
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0answers
34 views

Unbalanced data on fire for a binary classifier

I have a lot of training data from which I want to build a binary classifier, but the classes are highly unbalanced, 97% in one class, 3% in the other (even though, in absolute terms, I still have a ...
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1answer
65 views

Can a covariance matrix be recalculated for dummy variables?

Say I have the following sample from a continuous variable $X$ and a categorical (dichotomous) variable $Y$: X Y 0.5 1 2.3 2 2.2 2 1.8 1 Moreover, the covariance matrix between $X$ and $Y$ is also ...
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2answers
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Is it possible to compare continuous vs. dichotomous decisions in a meaningful way, that doesn't come down to different kinds of analyses?

I'm interested in finding out how the factors that contribute to a person's decision change when they are making a continuous vs. a dichotomous choice. However, I'm concerned that these two types of ...