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Does the bag-of-words representation ignores the order of the words in a text?
The bag-of-words model is a simplifying representation used in natural language processing and information retrieval (IR). In this model, a text (such as a sentence or a document) is represented as the bag (multiset) of its words, disregarding grammar and even word order but keeping multiplicity.
What type of data does bag-of-words represent?
A bag-of-words is a representation of text that describes the occurrence of words within a document. It involves two things: A vocabulary of known words. A measure of the presence of known words.
What are the limitations of the bag-of-words features in sentiment classification?
Although Bag-Of-Words model is the most widely used technique for sentiment analysis, it has two major weaknesses: using a manual evaluation for a lexicon in determining the evaluation of words and analyzing sentiments with low accuracy because of neglecting the language grammar effects of the words and ignore …
What happens when a categorical variable is masked?
Variables with such levels fail to make a positive impact on model performance due to very low variation. If the categorical variable is masked, it becomes a laborious task to decipher its meaning. Such situations are commonly found in data science competitions.
How to choose a model with categorical variables?
Since you provide little information about your categorical variables, for example how many levels each categorical variable have or how you do label encoding (just out-of-the-box method?) it is hard to give better guidelines.
How many variables are in a categorical dataset?
The dataset has a total of 7 independent variables and 1 dependent variable which I need to predict. Out of the 7 input variables, 6 of them are categorical and 1 is a date column.
How is a dummy variable represented in a categorical variable?
‘Dummy’, as the name suggests is a duplicate variable which represents one level of a categorical variable. Presence of a level is represent by 1 and absence is represented by 0. For every level present, one dummy variable will be created.