Calculating the weight of a word in each message - 7.3

Machine Learning
Version
7.3
Language
English
Product
Talend Big Data
Talend Big Data Platform
Talend Data Fabric
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Module
Talend Studio
Content
Data Governance > Third-party systems > Machine Learning components
Data Quality and Preparation > Third-party systems > Machine Learning components
Design and Development > Third-party systems > Machine Learning components
Last publication date
2024-02-21
Deprecated

Procedure

  1. Double-click the tModelEncoder component labelled tf to open its Component view.
  2. Repeat the operations described previously over the tModelEncoder labelled Tokenizer to add the sms_tf_vect column of the Vector type to the output schema and define the transformation as displayed in the image above.
    In this transformation, tModelEncoder uses HashingTF to convert the already tokenized SMS messages into fixed-length (15 in this scenario) feature vectors to reflect the importance of a word in each SMS message.