SentimentExtractor Arguments - Teradata Vantage

Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
8.00
1.0
Published
May 2019
Language
English (United States)
Last Update
2019-11-22
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B700-4003
lifecycle
previous
Product Category
Teradata Vantage™
TextColumn
Specify the name of the input column that contains text from which to extract sentiments.
InputLanguage
[Optional] Specify the language of the input text:
Option Description
'en' (Default) English
'zh_CN' Simplified Chinese
'zh_TW' Traditional Chinese
ModelFile
[Optional] Specify the model type and file. The default model type is dictionary. If you omit this argument or specify dictionary without dict_file, then you must specify a dictionary table with alias 'dict'. If you specify both dict and dict_file, then whenever their words conflict, dict has higher priority.

The dict_file must be a text file in which each line contains only a sentiment word, a space, and the opinion score of the sentiment word.

If you specify classification model_file, then model_file must be the name of a model file created and installed on the ML Engine by the function SentimentTrainer.

Accumulate
[Optional] Specify the names of the input columns to copy to the output table.
AnalysisType
[Optional] Specify the level of analysis—whether to analyze each document (the default) or each sentence.
Priority
[Optional] Specify the highest priority when returning results:
Option Description
'NONE' (Default) Give all results same priority.
'NEGATIVE_RECALL' Give highest priority to negative results, including those with lower-confidence sentiment classifications (maximizes number of negative results returned).
'NEGATIVE_PRECISION' Give highest priority to negative results with high-confidence sentiment classifications.
'POSITIVE_RECALL' Give highest priority to positive results, including those with lower-confidence sentiment classifications (maximizes number of positive results returned).
'POSITIVE_PRECISION' Give highest priority to positive results with high-confidence sentiment classifications.
OutputType
[Optional] Specify the kind of results to return:
Option Description
'ALL' (Default) Return all results.
'POSITIVE' Return only results with positive sentiments.
'NEGATIVE' Return only results with negative sentiments.