In a multinomial naive Bayes classifier, is the feature vector always a histogram? In the Wikipedia definition, the feature vector is defined as a histogram, as well as in this popular and well-done YouTube video.
However, if the features are words, then the variable is nominal and, therefore, the distribution cannot be estimated by a histogram (rather, it would be a bar chart).
Are these two sources wrong?
Edit: I've added the time code for the video

As ${\bf x} = (x_1,\ldots,x_n)$  and $x_i$ represent the number of times the instance/word $i$ realizes, then the vector $x$ is a vector of counts.
Thus, yes, ${\bf x}$ would be a barplot and not a histogram.
