In broader sense - synonym of "dichotomous data": any data that can take on only one of two values. In narrower sense - dichotomous data coded as 1 or 0; furthermore, sometimes "1" is supposed to mean "is present" and "0" to mean "is absent", which may require handling the two values asymmetrically ...

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8 views

Synthetic Minority Oversampling with Binary Features in the data

I am planning to use SMOTE or ADASYN for creating synthetic observations for a classification problem as the data is imbalanced. The question is, there are Binary variables in the Feature set, and I ...
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0answers
21 views

Appropriate classification model for combination of continuous, binary and categorical inputs

I have a binary classification problem for classify my samples to two classes (class_1 and class_2). I have different kinds of ...
1
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1answer
44 views

Ratio between positive and negative examples in a training problem

When training a 0/1 classifier, what should be the ratio of positive to negative, how to decide the ratio between them based on the classifier I use and the data set under analysis?
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0answers
8 views

Kernel Methods for Binary Vectors

I am currently involved in a project which requires a minor point in choosing a proper similarity metric for a set of binary vectors, i.e. all components are either 1 or 0 . Currently, the go-to ...
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0answers
11 views

Binary Response Models & sample data that contain a disproportionate number of 0's

Sorry in advance if this seems like a dumb question, but I am new to data modeling. I am attempting to classify customer usage as either a case of fraud or legitimate activity. I have attempted to ...
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0answers
34 views

Effect of binary variables on binary outcomes

All I have two sets of data. One where people bought and another where they did not. For each sample in the two sets, I have ~3000 binary independent variables. Each dataset has about 1000 samples. ...
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0answers
14 views

How to determine significance across categories of binary data?

I have subjects that fit into one of three, mutually exclusive groups, "favorable," "intermediate," and "unfavorable" based on their genetics. They can then be classified as either a "responder" or a ...
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1answer
26 views

Optimizing for target metrics in Weka

I'm a PhD student in Information Retrieval with some limited experience in ML. We've been working on a binary classification task with weka (I'm using weka programmatically via Java), specifically ...
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0answers
24 views

How to analyse binary outcome data with between- and within subjects factors?

I am looking for the right statistical procedure to analyse my data (mixed design) with binary outcomes. Between-subjects variable: treatment (yes or no); experimentally manipulated Within-subjects ...
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0answers
19 views

zinb estimates change when using factor variables

I use Stata SE 13 and I have a problem with the command zinb in Stata. I have binary variable female which is 1 if respondent is female, 0 otherwise (no other ...
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0answers
10 views

test to be applied

I have applied 3 treatments at 10 different concentrations of each on a bacteria to see if they affect its existence. my response variable is binary i.e. 1 for effective and 0 for ineffective. basic ...
2
votes
1answer
51 views

c-index for parametric links in binary regression

I am conducting a binary regression using different sorts of parametric links (logistic, Pregibon, Aranda-Ordaz, ... see) and I would like to compare their predictive and classification perfomance in ...
3
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1answer
67 views

Cross correlation for very sparse binary data

I have a very large (5271159x60) sparse (~2.5%) binary matrix, and I'd like to calculate the cross correlation between each of the columns (sensors) for a series of lags from -10:10, which would give ...
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2answers
44 views

Fitting decaying exponential to binary response

I have this data that I want to fit with $y = e^{-bx}$, but the y:s represent probabilities and the outcomes are either 0 or 1, so I can't say $ln (y) = -bx$ since the values will just alternative ...
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0answers
29 views

Make a classification dataset with binary features using scikit-learn

I would like to illustrate a classification algorithm by using this algorithm on a 2-class dataset with binary n-dimensional features. In the past, I have used the scikit function make_classification ...
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1answer
118 views

Probability distribution of binary time series

I am unable to understand concepts related to the probability distribution of binary time series. This is from the book Binary time series by Benjamin Kedem, vol 52 Let $X_t$, t =0,1,... be a binary ...
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0answers
44 views

Two step cluster analysis and a binary matching coefficient

I want to commence a two-step cluster analysis, since the database I am conducting analysis on contains important metric as well as nominal values. => Question #1: Should the binary and the metric ...
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0answers
14 views

analysis strategy for selecting and/or transforming correlated continuous biomarkers to predict binary endpoint

I am given a simulation task to come up with several analysis strategies and compare their relative performances. The horizon is wide open; I appreciate all recommendations of methods and references. ...
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1answer
216 views

Hierarchical or Two-step cluster analysis for binary data?

(This question is an edited version of a question I previously posted which one user recommended would benefit from more focus). I have 2000 questionnaires from respondents which ask 33 different ...
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0answers
17 views

Cluster analysis of binary data [duplicate]

I have 2000 questionnaires from respondents which ask 33 different questions about which issues are present in their lives - i.e. alcohol abuse, domestic violence, mental health, child abuse, learning ...
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0answers
26 views

Feature boosting via rescaling in logistic regression and linear SVMs

If I were expressing a problem in terms of binary features, all encoded as {0,1}, could I boost some features by encoding them as {0,2}? Would the effect change based on whether I used either of the ...
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0answers
55 views

Identifiability in generalized linear random effect model?

Suppose I observe binary $Y_{ij}$ for $i = 1, ..., N$ and $j = 1, ..., J$ and I want to model $$\Pr(Y_{ij} = 1 \mid \lambda_{i}) = \Phi(\lambda_{ij}), \qquad [Y_{ij} \perp Y_{ij'} \mid \lambda_i]$$ ...
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1answer
26 views

Correlation or clustering of continuous score and discrete variable states

I have an experiment that produces a decimal score representing quality, and a bunch (5-30) of variables that each take on one of a set of discrete states. - The states are not meaningfully ...
4
votes
1answer
100 views

Closed form expression for count of “runs” in binary sequence sharing same length, number of 1's, and location of final 1

I am struggling with the following combinatorial problem related to research I am doing. Take a binary sequence $(y_1, y_2, \ldots, y_n)$ of length $n$ with $x$ $1$'s, where the final $1$ is in ...
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0answers
21 views

Binary event probability optimization

I have a relatively small sample of binary events (50-100 events) that occurred during a time of day (the success rate is closely related to the time of day). I'm grouping these events into hour ...
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0answers
10 views

Advice on finding features of users who converted vs. users who didn't?

I'm a programmer (comfortable in Python and R) and I'm getting started with machine learning methods. I have a lot of data from the past year about users on my site. About 50% of the users converted ...
2
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2answers
104 views

Which classifiers work well with unbalanced data?

I have a binary classification problem which is very unbalanced - it can have 98% of data from one class. Which classifiers work well with this sort of data? I have an unlimited supply of training ...
2
votes
1answer
41 views

Only binary predictors — ANOVA, regression, or other?

I am trying to fit a model to predict a quantitative response variable, using several binary variables. In particular, I am interested in measuring the relationship between one of the binary variables ...
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votes
1answer
37 views

R - Analyzing Relationship Between Two (or more) Binary Variables

Say I have two vectors: Action.Taken = c(0,1,0,0,1,1,0,1,0) Success = c(0,0,0,1,0,1,0,1,0) The first tells me whether or not a specific action was taken in a ...
3
votes
3answers
68 views

Test for aggregation of binary events/successes (binomial/glm??)

this has been vexing me for a while and I can't seem to solidify an answer beyond vague thoughts about Poisson distributions. I think this is a simple problem and I'm missing something obvious. Any ...
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votes
2answers
71 views

How to deal with a skewed class in binary classification having many features?

I am doing data analysis in the mobile ad targeting domain. I have around 18 features and for a combination of these features, the result is either True or False (1/0) depending on whether the ...
1
vote
1answer
43 views

How to analyze two-way within subjects design with binary data

I am interested in testing how users perform on three different user interfaces. On each of the three interfaces, a person will try 12 Tasks. So each participant will do Task 1 three times, Task 2 ...
0
votes
2answers
80 views

Best way to test for co-occurrence of measures

I have some data with temporal measures over time. I'd like to test whether two binary variables co-occur more often than chance would predict, and I'm wondering the best (simple) way to do that. The ...
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0answers
78 views

What to Do When a Log-binomial Model's Convergence Fails

There are times when one might want to estimate a prevalence ratio or relative risk, in preference to an odds ratio, for data with binary outcomes - say, if the outcome in question isn't rare, so the ...
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0answers
271 views

Regression analysis with binary independent variables

Should one use regression analysis when all independent variables are binary categorical (0,1) to see their effect on continuous dependent? Some suggest that regression shouldn't be used in this case. ...
0
votes
1answer
424 views

PCA on Binary Data

I having binary data set (yes/no), so can I apply PCA on that. Is it mathematically correct to do that. In my opinion Binary variable can only be subjected to logical operations, so how it can be ...
4
votes
1answer
269 views

Is it meaningful to calculate Pearson or Spearman correlation between two Boolean vectors?

There are two Boolean vectors, which contain 0 and 1 only. If I calculate the Pearson or Spearman correlation, are they meaningful or reasonable?
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votes
1answer
45 views

How to analyze relationship between a nominal variable (2 values) and a numerical variable (integer)?

I'm trying to find out if a nominal variable A (2 values: x and y) and a numerical variable ...
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0answers
41 views

Stratified Cross-Validation with Collaborative Filtering

My dataset consists of binary preferences ($0$ or $1$) given by users on items like this: User-ID | Item-ID | Preference If a user has not given a preference to an item, then it is not in ...
0
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0answers
20 views

Implementation of semi parametric methods

Has anyone worked with semi parametric methods to estimate parameters with binary outcome? Examples are like Cosslett (1983) or Ichimura or Klein-Spady. In other words we are looking for semi ...
1
vote
1answer
86 views

Paired test for comparing boolean data

I have $n$ individuals, and for each individual, I have two measurements using two devices (device X and device Y). I know the ground truth for the correct measurement, and I can classify each ...
0
votes
0answers
54 views

Hypothesis test for comparing two F-measures

I have a classifier that classifies each sample point as positive or negative. Suppose I am evaluating it on a limited data set where I have ground truth and then computing the F-measure ...
1
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1answer
95 views

How do you correlate binary & ordinal variables?

Which test to use to calculate correlations between them? Cramer's V, Kruskal-Wallis, or something else?
0
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0answers
20 views

I have data that includes a record of each event and its time

I want to see if this other data I have predicts that this first event will occur. In other words, I have a data field with a record of farts, with columns for day, month, year, and then I have ...
0
votes
0answers
50 views

What's the meaning of the class indicator matrix when transforming the class label matrix into it in canonical correlation analysis?

When using canonical correlation analysis (CCA), we can integrate the dataset and label information via transforming the class label matrix Y into the class indicator matrix T. Such as: $T = ...
2
votes
0answers
37 views

Comparison of point-biserial and linear correlation coefficients

I have a continuous variable X that is associated with a continuous outcome Y and a dichotomous outcome Z. If I calculate Pearson's $r$ between X and Y, and the point-biserial coefficient $r_{pb}$ ...
0
votes
0answers
197 views

Output probabilities of binary support vector machine classifier in Matlab R2014a

I’m using SVM for classification of my binary output problem. I want probability of belonging to every class. How can I obtain it? For instance suppose this is our structure: ...
0
votes
0answers
95 views

Running a Pearson's correlation calculation on binary survey data

I have the following raw survey data output from a survey app: I was asked to run a Pearson's R on the results (1s and 0s). The format that is returned is as follows: I was further ...
1
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0answers
64 views

Prediction method where predictors and response variable are binary

I have a group of binary tasks performed by multiple subjects. Every task can be either performed right or wrong (i.e.,1/0). My goal is to predict the accuracy of future task given the performance on ...
3
votes
2answers
518 views

Logistic regression vs. LDA as two-class classifiers

I am trying to wrap my head around the statistical difference between Linear discriminant analysis and Logistic regression. Is my understanding right that, for a two class classification problem, LDA ...