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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.

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I'm watching a lecture on applying kNN to the digit recognition (MNIST dataset) problem. Let's say $n$ denotes the number of neighbors. This is a multiclass classification problem, so having an odd …
asked Mar 24 by Shirish Kulhari
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Let's say I'm trying to evaluate a classification algorithm and suppose there are $m$ data points in my test set. Here's my understanding so far: assuming my evaluation metric is the classification … error, I can form a Bernoulli random variable $X$ with success probability $p$. We treat a correct classification as a "success". This means $p$, which is the population proportion of successes, can …
asked May 24 by Shirish Kulhari