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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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8 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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0answers
18 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
26 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
26 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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0answers
19 views

Chi Square - alternative for three-way interaction

I am interested in the effect of predictability and expected value on the choice between two payment options. Basically, I have a 2(predictability of the payment option: predictable vs. unpredictable; ...
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0answers
14 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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0answers
4 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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0answers
7 views

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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0answers
9 views

Imputing binary missing data with hmi and mice — Error: C stack usage 7969776 is too close to the limit [migrated]

I'm running HMI on two level data (students in courses) with missing data at the student level. The code throws the following error (Error: C stack usage 7969776 is too close to the limit) when I ...
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1answer
49 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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0answers
10 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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0answers
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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0answers
35 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
52 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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0answers
21 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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0answers
25 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
30 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
26 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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0answers
12 views

Shadow significance

I've faced specific issue recently and kindly ask you to help. Imagine standard linear supervised learning framing for binary classification problem (X,y, OLS, p-vals, etc.). One can develop common ...
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2answers
61 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
27 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
38 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
34 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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0answers
18 views

Could I use calinski harabaz score to evaluate clustering results when target data is binary data?

My target data is binary data, the size is 17000*500, after using hierarchical clustering, could I use calinski harabaz score to evaluate clustering results?
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0answers
31 views

How to find patterns in binary data set?

I have a data set of movement (rotation around 360 degree axis)of an object .I just need to find a pattern with in the data so that I can predict out which all regions get triggered when the object ...
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1answer
39 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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0answers
17 views

Identify clusters with specific properties in binary matrix

My question is somewhat similar to this one, but has some properties specific to it that I think makes it a non-duplicate. I have a binary matrix of nominal categorical values for a set of users: <...
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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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0answers
39 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
41 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
36 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
32 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
50 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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0answers
20 views

Compare two groups: repeated measurements with binary outcomes

I am unsure what test to use in SPSS to anaylze my data set. Two groups (Group 1 = 36 patients, group 2 = 42 patients), repeated measurements at 9 time points (some time intervals between time points)...
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2answers
48 views

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 ...
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0answers
30 views

Generate Keys with diverse [closed]

I am working on program that on one of the step I need to generate a key(256)bits to encrypt something. The key has to be unique in specific way . The key has to be binary[1,0,1..], (256)bits long ,...
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0answers
10 views

Methodology for comparing FEC campaign finance sources with candidates' votes on legislation

I am trying to compare a database of campaign finance contributions to candidates with a database of congressional votes, and see if I can unearth any causal relationships between campaign finance ...
2
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1answer
93 views

Binary predictor with highly skewed distribution

I am running a linear regression model and I have a binary predictor that has a highly skewed distribution. For example, one category represents 96% of the data. In terms of frequency, the other 4% ...
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0answers
24 views

Is there any statistical problem on instrumental variable analysis with binary exposure and binary outcome?

I would like to conduct an instrumental variable (IV) analysis (a.k.a Mendelian Randomization analysis due to my IV is a genetic variant). In many cases as I searched before, an IV analysis was ...
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0answers
24 views

Binary logistic regression with and without Generalised Estimated Equations (GEE)

I have two questions which are related so will include them as one. So I have repeated measures data (pedestrians rejecting and accepting gaps on a road, the rejected gaps are repeated measures ...
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0answers
9 views

Tests for mediation between Binary DV and binary IV by a continuous mediator

This is my first time working with binary outcomes in R and I'd be grateful for some advice. I've got an experiment where subjects are in 1 of 2 conditions (A or B) and either succeed or fail in a ...
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0answers
19 views

How could a variable length binary string be encoded as an SVM feature?

I have data which is a binary string, e.g. 10001001 or 111100000001. The length can vary between 3 and 13 characters in length. It represents a pattern found in nature where the length is variable ...
2
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1answer
42 views

How to present results of 2 binary experiments?

I have two experiments E1 and E2. Each consists of several trials (number of trials is different between experiments). Each ...
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2answers
46 views

Correlation between two binary data sets

I am unsure how to do this properly. I have two binary data sets, i.e. values in each data set is either 1 or 0. I now wish to see if they are in any way correlated. I could use Pearson's, but I don't ...
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1answer
67 views

R: logistic regression residual deviance higher and null deviance but predictors all significant interpretation

I am running a logistic regression, but for a group of predictors I tried, all of then are highly significant but the residual deviance is much higher than the null deviance. ...
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2answers
72 views

Why we use log function for cross entropy?

I'm learning about a binary classifier. It uses the cross-entropy function as its loss function. $y_i \log p_i + (1-y_i) \log(1-p_i)$ But why does it use the log function? How about just use linear ...
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1answer
271 views

How do I cluster data according to Hamming distance

I've a list of binary strings and I'd like to cluster them in Python, using Hamming distance as metric. I also would like to set the number of centroids (i.e. clusters) to create. Which algorithm do ...
2
votes
1answer
34 views

glmer with binary dependent variable: assumptions and model convergence

I am new to generalized linear mixed models, and I am currently analyzing the effect of various fixed effects (three main and their two-way interactions) on a binary variable (0=behaviour absent, 1=...
2
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0answers
245 views

Is MCA equivalent to PCA when all variables are binary?

I am looking to apply principal component analysis on binary (true/false) data, and I have come across the "equivalence between PCA and MCA" (Multiple Correspondense Analysis) for binary data, but ...