Tech Notes

My notes on Statistics, Big Data, Cloud Computing, Cyber Security

Tag Archives: conditional probability

Conditional Probability, Bayes Theorem, Naive Bayes Classifier

Both kNN and NaiveBayes are classification algorithms. Conceptually, kNN uses the idea of “nearness” to classify new entities. In kNN ‘nearness’ is modeled with ideas such as Euclidean Distance or Cosine Distance. By contrast, in NaiveBayes, the concept of ‘probability’ is used to classify new entities.

Before someone can understand and appreciate the nuances of Naive Bayes’, they need to know a couple of related concepts first, namely, the idea of Conditional Probability, and Bayes’ Rule. (If you are familiar with these concepts, skip to the section titled Getting to Naive Bayes’)

Conditional Probability in plain English: What is the probability that something will happen, given that something else has already happened. Read more of this post

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Probability

Used for Understanding and Quantifying Randomness.

A probability provides a quantitative description of the likely occurrence of a particular event. Probability is conventionally expressed on a scale from 0 to 1; a rare event has a probability close to 0, a very common event has a probability close to 1.

It is a measure or estimation of likelihood of occurrence of an event

Probability deals with predicting the likelihood of future events, while statistics involves the analysis of the frequency of past events.

Probability is primarily a theoretical branch of mathematics, which studies the consequences of mathematical definitions. Statistics is primarily an applied branch of mathematics, which tries to make sense of observations in the real world.

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