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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
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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_ …
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 …
5
votes
1
answer
249
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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 ke …
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. …