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Naïve Bayes Supervised AI model

Naïve Bayes Supervised AI model.

Naïve Bayes Supervised AI model described the organization’s internal mail system/tweets or, the number of users, and if known, an estimate of the number of daily emails (volume). Re-use the “training data” i.e. classified examples (words) to create a list of “features” (independent variables).
For each of the independent variables “words” create a listing with these features:
Explain what each of independent variable “words” means
Prioritize each of the independent variable “words”
Explain why each of the independent variable “words” is true

For each of the dependent variables “words” create a listing with these features:
Explain what each of dependent variable “words” mean
Prioritize each of the dependent variable “words”
Explain why each of the dependent variable “words” is true

For each of the irrelevant variables “words” create a listing with these features:
Explain what each of irrelevant variable “words” mean
Prioritize each of the irrelevant variable “words”
Explain why each of the irrelevant variable “words” is false

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Naïve Bayes Supervised AI model

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