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Detecting Fake News with Python
What is Fake News?
A type of yellow journalism, fake news encapsulates pieces of
news that may be hoaxes and is generally spread through social media and other
online media. This is often done to further or impose certain ideas and is
often achieved with political agendas. Such news items may contain false and/or
exaggerated claims, and may end up being viralized by algorithms, and users may
end up in a filter bubble.
What is a Tfidf Vectorizer?
TF
(Term Frequency): The number of times a word appears in a document is its
Term Frequency. A higher value means a term appears more often than others, and
so, the document is a good match when the term is part of the search terms.
IDF
(Inverse Document Frequency): Words that occur
many times a document, but also occur many times in many others, may be
irrelevant. IDF is a measure of how significant a term is in the entire corpus.
The TfidfVectorizer converts
a collection of raw documents into a matrix of TF-IDF features.
What is a Passive Aggressive Classifier?
Passive Aggressive algorithms are
online learning algorithms. Such an algorithm remains passive for a correct
classification outcome, and turns aggressive in the event of a miscalculation,
updating and adjusting. Unlike most other algorithms, it does not converge. Its
purpose is to make updates that correct the loss, causing very little change in
the norm of the weight vector.
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