A simple explanation of Naive Bayes Classification [closed]

The accepted answer has many elements of k-NN (k-nearest neighbors), a different algorithm. Both k-NN and NaiveBayes are classification algorithms. Conceptually, k-NN uses the idea of “nearness” to classify new entities. In k-NN ‘nearness’ is modeled with ideas such as Euclidean Distance or Cosine Distance. By contrast, in NaiveBayes, the concept of ‘probability’ is used … Read more

What is the most effective way for float and double comparison?

Be extremely careful using any of the other suggestions. It all depends on context. I have spent a long time tracing bugs in a system that presumed a==b if |a-b|<epsilon. The underlying problems were: The implicit presumption in an algorithm that if a==b and b==c then a==c. Using the same epsilon for lines measured in … Read more

What is the difference between a generative and a discriminative algorithm? [closed]

Let’s say you have input data x and you want to classify the data into labels y. A generative model learns the joint probability distribution p(x,y) and a discriminative model learns the conditional probability distribution p(y|x) – which you should read as “the probability of y given x“. Here’s a really simple example. Suppose you … Read more

How do I create a URL shortener? [closed]

I would continue your “convert number to string” approach. However, you will realize that your proposed algorithm fails if your ID is a prime and greater than 52. Theoretical background You need a Bijective Function f. This is necessary so that you can find a inverse function g(‘abc’) = 123 for your f(123) = ‘abc’ … Read more

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