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can someone help me with this question In your data base you have N examples from the first class (“good”) and M examples
from the second class (“bad”). In real life we know that the frequency of good cases is q and the
frequency of bad cases is 1-q (the proportion of good and bad cases in your data base may be different
from the real life). Let the kNN classifier give you k nearest neighbours from your data base for a
given case with unknown class. From these k nearest neighbours v are of the good class and w=k-v of
the bad class. How will you evaluate the probability that your example is “good”?
8 years ago

Maths Question asked by Khaznah

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The probality that it is good depends on the initial listed values
Answered by [Deleted Member]
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