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Statistical classification is the problem of identifying the sub-population to which new observations belong, where the identity of the sub-population is unknown, on the basis of a training set of data containing observations whose sub-population is known. Therefore these classifications will show a variable behavior which can be studied by statistics.

1 vote

How to combine the results of several binary tests?

To simplify a bit, let's assume that you only have two diagnostic tests. You want to calculate $$ \Pr(\text{Disease} \mid T_1,T_2) = \frac{\Pr(T_1,T_2 \mid \text{Disease})\Pr(\text{Disease})}{\Pr(T_ …
fgregg's user avatar
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3 votes
0 answers
83 views

What's a good range of weights to evaluate for $L_2$ regularized logistic regression?

I want to find a weight that minimizes an averaged cross validated misclassification score from an $L_2$ logistic regression classifier. Obviously, the search space for the weights should be bounded b …
fgregg's user avatar
  • 1,200
5 votes
1 answer
249 views

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 ke …
fgregg's user avatar
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6 votes

Is cosine similarity a classification or a clustering technique?

Many classification and clustering methods depend upon some measure of distance and similarity or distance between objects. If they do, then they can use cosine similarity. …
fgregg's user avatar
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