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Results tagged with categorical-encoding
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user 238499
Representing categorical variables as sets of numerical variables. Necessary in many types of analysis for them to process categorical data. A common example is using a categorical predictor in regression/ANOVA via dummy coding, effect coding, Helmert coding, user-defined contrasts, etc.
0
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interpreting coefficients of interaction terms between categorical variables
You are absolutelly right, it is exactly as you posted it (assuming other_var is equal to 0, otherwise you will have to add $b_4 * othervar$)
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When finding significance in parts of a categorical variable during stepwise selection, do y...
You could in principle put types 1, 2 and 3 as a single group, but I don't know if this makes sense in your particular case.
Also, please remember that statistical significance is an arbitrary tresh …
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6
votes
Accepted
Clear explanation of dummy variable trap
Let's say you have a binary variable, like sex. You create two dummy variables to reflect that in your model. Let's say you have six individuals $(M,F,F,M,M,F)$. Your dummy variables look like:
$X_1 …
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0
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Regression/classification models and dummy variables
Assuming you're using the base R lm/glm functions:
If you createthe dummy variables yourself, the step process will treat them as separate variables, so you may get some of them removed while the othe …
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How to interpret regression function with categorical variable?
The category variable coefficients indicate how much your prediction is incremented if a given individual belongs to the corresponding category.
What strikes me is that you have two different coeffic …
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How to encode categorical variables in a video game predictive model
If the only possible results are win/lose, then you are in front of a binary classification problem (so SVM, trees, logistic regression and all of the others can apply). I don't know about scikit-lear …
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