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Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression

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Flexible version of logistic regression

If you want a classification technique that is insensitive to the relative proportion of examples from different classes, Support Vector Machines have that property as do decision trees.
fgregg's user avatar
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5 votes
1 answer
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Constrain decision boundary to fall on grid lines in multiple class logistic regression

I would like to use multiple class logistic regression to learn the decision boundaries separating the different classes (denoted by color) in the image below. … Kernel logistic regression with a RBF kernel seems like a good choice, but I would like the decision boundary, when projected back to the 2-d space, to fall along the white grid lines. …
fgregg's user avatar
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20 votes
2 answers
13k views

Logit with ordinal independent variables

In a logit model, is there a smarter way to determine the effect of an independent ordinal variable than to use dummy variables for each level?
fgregg's user avatar
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8 votes

Independent variables in ordinal logistic regression

Let's think about regular linear regression, and to make it concrete, let's say we are trying to predict height of people. When you regress heights against just an intercept term and no predictors, th …
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