Standard lists are used by scripts to identify standard, valid values for predictions. Standard lists are also used to identify words that need to be removed or modified during a script's text cleaning process before they negatively impact predictions.
Words in a standard list can be mapped to a standard value. Additionally, a weight can be added as a word's property to affect how likely it is to be selected in a fuzzy logic script's prediction.
The following image shows a portion of the failure mechanism standard list.
In the failure mechanism standard list, Blockage/Plugged in the Standard Value column is a standard value to which multiple words are mapped. If one of the mapped words in the Word column is found by a fuzzy logic script that uses the failure mechanism standard list, the script is likely to provide a predicted value of Blockage/Plugged.
When fuzzy logic and machine learning scripts are executed, the text of the input words is cleaned. Some extraneous words are removed to eliminate noise, and some words are modified for consistency (e.g., the contraction didn't is modified to be did not).
The following image shows the stopwords standard list that is used to identify noise words to be removed during text cleaning.
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