Describe the steps for the Naïve Bayes Algorithm

Expert Solution

Bayes Naive uses a method to predict the probability of different classes in different traits. This algorithm is mainly used in text classification and has problems with multiple classes.

Classifier Naive Bayes assumes that the presence of a particular function in a class is not related to the presence of any other function. The Naive Bayes model is easy to build and especially useful for very large data sets.

Steps: -

1. Converts the data placed in the frequency table.

2. Create a probability chart by finding probabilities such as the odd probability and the probability of the game.

3. Now use the Naive Bayes equation to calculate the back probability of each. The outcome of the prediction is very likely.

This algorithm is also known as many predictive functions. Here you can predict the different types of goals that will change the target. This algorithm requires a smaller scale to calculate the required parameters.

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keosha answered 6 months ago

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