| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263 |
- function x = emailFeatures(word_indices)
- %EMAILFEATURES takes in a word_indices vector and produces a feature vector
- %from the word indices
- % x = EMAILFEATURES(word_indices) takes in a word_indices vector and
- % produces a feature vector from the word indices.
- % Total number of words in the dictionary
- n = 1899;
- % You need to return the following variables correctly.
- x = zeros(n, 1);
- for i = 1:length(word_indices)
- x(word_indices(i)) = 1;
- end
- % ====================== YOUR CODE HERE ======================
- % Instructions: Fill in this function to return a feature vector for the
- % given email (word_indices). To help make it easier to
- % process the emails, we have have already pre-processed each
- % email and converted each word in the email into an index in
- % a fixed dictionary (of 1899 words). The variable
- % word_indices contains the list of indices of the words
- % which occur in one email.
- %
- % Concretely, if an email has the text:
- %
- % The quick brown fox jumped over the lazy dog.
- %
- % Then, the word_indices vector for this text might look
- % like:
- %
- % 60 100 33 44 10 53 60 58 5
- %
- % where, we have mapped each word onto a number, for example:
- %
- % the -- 60
- % quick -- 100
- % ...
- %
- % (note: the above numbers are just an example and are not the
- % actual mappings).
- %
- % Your task is take one such word_indices vector and construct
- % a binary feature vector that indicates whether a particular
- % word occurs in the email. That is, x(i) = 1 when word i
- % is present in the email. Concretely, if the word 'the' (say,
- % index 60) appears in the email, then x(60) = 1. The feature
- % vector should look like:
- %
- % x = [ 0 0 0 0 1 0 0 0 ... 0 0 0 0 1 ... 0 0 0 1 0 ..];
- %
- %
- % =========================================================================
-
- end
|
