SL Naive Bayes classifier Flashcards
An approximation of a relationship between an input and an output
Model
An approach to finding a solution which is typically faster but less accurate than optimal solution
Heuristic
A distribution which evaluates a particular outcome as binary
Bernoulli Distribution
Indicates the probability of a particular class regardless of the features of some example
Prior
The probability of some features given a particular class
Likelihood
The denominator of the Naive Bayes classifier
Evidence
The probability of a class given some features
Posterior
The list of words that the Naive Bayes classifier recognizes
Vocabulary
A type of additive smoothing which migrates the chance of encountering zero probabilities within the Naive Bayes classifier
Laplace Smoothing
The splitting of some raw textual input into individual words or elements
Tokenization
The process of transforming raw inputs into something a model can perform training and predictions
Featurization
Used in a step of featuring. It transforms some input into something else
Vectorizer
A word typically discarded which doesn’t add much predictive value
Stop word
Removing the ending modifiers of words leaving the stem of the word
Stemming
A more calculated form of stemming which ensures the proper lemma results from removing the word modifiers
Lemmatization
