Combining feature vectors - Cloud - 8.0

Machine Learning

Version
Cloud
8.0
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
2024-02-20

Procedure

  1. Double-click the tModelEncoder component labeled features_assembler to open its Component view.
  2. Repeat the operations described previously over the tModelEncoder labeled Tokenizer to add the features_vect column of the Vector type to the output schema and define the transformation as displayed in the image above.
    Note that the parameter to be put in the Parameters column is inputCols=sms_tf_idf_vect,num_currency,num_numeric,num_exclamation.
    In this transformation, tModelEncoder combines all feature vectors into one single feature column.