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Not improvement in representation of encoder in AE

My experience is that using the encoded representation of the autoencoder as input to the classifier usually does not improve classification. And the augmentations you have described might make the ...
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0 votes

How to define categories from a continuous variable which affect overall survival

Instead of categorizing your continuous variable to create survival curves for each group, you might be interested in graphical displays that directly represent the continuous nature of the variable. ...
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  • 51
6 votes

Are coordinates (e.g. Point(123, -123)) considered interval data?

The classification of measurements into nominal, ordinal, interval and ratio scales is sometimes helpful, but it has wasted a great deal of individual and collective time in pedagogy and polemics, if ...
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1 vote

Interpreting intercept with a categorical predictor

This is your model: $$\hat y = \beta_1+\beta_2 X_2+\beta_3 X_3+\beta_4 X_4+\beta_5 X_5+\beta_6 X_6$$ Since you are using R's defaults, that implies your categorical variable is encoded with a contrast ...
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0 votes

Can eta squared be used for comparing effect size of a categorical (>2 categories) and continuous variable?

@Brittany Hite: Be carefull not to use betas directly to assess the influence/strength of predictor variables, since they depend on the unit used to measure the variable. For example, if you want to ...
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1 vote
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Why does MatchIt can calculate mean on a factor column?

For categorical variables, MatchIt reports the proportion of observations in each category, separately for the treated and the controls. For binary variables, it reports the proportion of ...
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11 votes

Do Statistical Binning Algorithms Exist?

The most rational and elegant solution, and best performing in terms of mean squared error of estimates, is to use a method that borrows information across groups: either penalized maximum likelihood ...
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1 vote

Removing categorical predictors with mode frequency above certain threshold

I don't think it is possible to come up with a good, general rule of thumb for this. Imagine a disease/condition that is perfectly determined by variation in one gene and is very rare. Suppose 0.01% ...
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0 votes

How to distinguish numerical categorical (Ex: White = 1, Latino = 2 etc) from numerical continuous or discrete variables on a dataset?

I found this helpful A key distinction between ordinal categorical variables and discrete quantitative variables is that there is a uniform degree of difference within discrete quantitative variables. ...
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2 votes

How to do mediation analysis when dependent variable is categorical

Your regression method for evaluating outcome is presumably multinomial logistic regression. Thus you have multiple regression coefficients associated with your predictor variables, each representing ...
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2 votes
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Model suggestion alternative to categorical regression

First, have you prepared some visualizations of your data? Plotting the data points should always be the first step, this helps to gain insight into your data. A trivial pair-plot (in R e.g. ...
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1 vote
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Properly displaying Categorical Variables Represented as R Factors in a Table

These tables are often confusing, as you can tell from many questions on this site. Unless you have some experience with the treatment/dummy coding used by R as default, thus appreciating that the ...
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4 votes
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How to interpret categorical variable in logistic regression with contrast coding

It's best to choose variable coding on arbitrary convenience, then to get any contrast of interest by subtracting predicted log odds (and possibly anti-logging the difference to get an odds ratio). ...
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1 vote
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How can I statistically assess directionality for larger tables of count data (eg 2x3, 2x4)?

I think this could reasonably be analysed as a $2\times2\times2$ table using a Poisson log-linear model. You could start by defining a mutual independence model for the two decisions and condition. In ...
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1 vote
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Categorical or continuous? I can't decide

If your distances can indeed only take one of two values, then it does not make a difference. In either case, your model will estimate one parameter for distance. If you include distance as a ...
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