Output only. The sentiment with the semantic, as given to the
AutoMl.ImportData when populating the dataset from which the model used
for the prediction had been trained.
The sentiment values are between 0 and
Dataset.text_sentiment_dataset_metadata.sentiment_max (inclusive),
with higher value meaning more positive sentiment. They are completely
relative, i.e. 0 means least positive sentiment and sentiment_max means
the most positive from the sentiments present in the train data. Therefore
e.g. if train data had only negative sentiment, then sentiment_max, would
be still negative (although least negative).
The sentiment shouldn't be confused with "score" or "magnitude"
from the previous Natural Language Sentiment Analysis API.
Output only. The sentiment with the semantic, as given to the
AutoMl.ImportData when populating the dataset from which the model used
for the prediction had been trained.
The sentiment values are between 0 and
Dataset.text_sentiment_dataset_metadata.sentiment_max (inclusive),
with higher value meaning more positive sentiment. They are completely
relative, i.e. 0 means least positive sentiment and sentiment_max means
the most positive from the sentiments present in the train data. Therefore
e.g. if train data had only negative sentiment, then sentiment_max, would
be still negative (although least negative).
The sentiment shouldn't be confused with "score" or "magnitude"
from the previous Natural Language Sentiment Analysis API.
Output only. The sentiment with the semantic, as given to the
AutoMl.ImportData when populating the dataset from which the model used
for the prediction had been trained.
The sentiment values are between 0 and
Dataset.text_sentiment_dataset_metadata.sentiment_max (inclusive),
with higher value meaning more positive sentiment. They are completely
relative, i.e. 0 means least positive sentiment and sentiment_max means
the most positive from the sentiments present in the train data. Therefore
e.g. if train data had only negative sentiment, then sentiment_max, would
be still negative (although least negative).
The sentiment shouldn't be confused with "score" or "magnitude"
from the previous Natural Language Sentiment Analysis API.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-01-27 UTC."],[],[]]
