You want to create a machine learning algorithm to identify food recipes on the web. To do this, you create an algorithm that looks at different conditional probabilities. So if the post includes the word flour, it has a slightly stronger probability of being a recipe. If it contains both flour and sugar, is even more likely a recipe. What type of algorithm are you using?

Based on the above information, it can be inferred that I am using a Naive Bayes classifier algorithm since each variable is independently related to the conclusion.

What is a Naives Bayer algorithm?

Naive Bayes is a term that refers to a type of algorithm that is characterized by not establishing a relationship between the presence or absence of a particular feature with the presence or absence of any other feature.

This type of algorithm is characterized by considering each variable independently without interrelating the possibilities or characteristics of an element.

In this case, the characteristics that determine that it is a recipe are the words "flour" and "sugar" independently.

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OPTIONS

Naive Bayes classifier
K-nearest neighbor
Multiclass classification
Decision tree

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