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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Keyword Index</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>ada boost</string-name>
        </contrib>
      </contrib-group>
      <pub-date>
        <year>2018</year>
      </pub-date>
      <abstract>
        <p>Naive Bayes naive Bayes Naive Bayes (NB) Neural bag of Ngrams neural bag-of-Ngrams NLP NMF</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>Email spam embedding</title>
    </sec>
    <sec id="sec-2">
      <title>FastText</title>
      <p>handcrafted features
k-nearest neighbor (KNN)
Keras Embedding
logistic regression
logistic regression (LR)
long short-term memory (LSTM)
LSTM
machine learning
Metrics for Unbalanced Datasets
multi-layer perceptron (MLP)</p>
      <p>Performance of Teams
phishing
phishing email
Phishing emails
Random Forest
random forest (RF)
recurrent neural network (RNN)
Spam
support vector machine
support vector machine (SVM)
SVD
SVM (Support Vector Machine)
Term Frequency- Inverse Document Frequency
term frequency-inverse document frequency (tf-idf) doc2vec
Text Classi cation
tf-idf
vector space model
Word Embedding
word embedding
1
17, 51
28
41
33, 69
10
51
62
17
10
33, 69
33, 69
33, 69
10
22
17
10
22
51</p>
    </sec>
  </body>
  <back>
    <ref-list />
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