What is the importance of data cleaning in Artificial Intelligence?
Answer and explanation
Correct answer: It identifies and corrects or removes inaccurate, duplicate, incomplete, or irrelevant data, improving data quality.
Data cleaning prepares a dataset by finding errors, duplicates, missing values, inconsistent formats, and irrelevant records. Appropriate correction, removal, or documentation makes the remaining data more suitable for analysis and training. Option A is correct. Cleaning does not eliminate all data or allow prediction without data; it improves the quality of useful data.
Frequently asked questions
What is the correct answer to this question?
It identifies and corrects or removes inaccurate, duplicate, incomplete, or irrelevant data, improving data quality.
Why is this the correct answer?
Data cleaning prepares a dataset by finding errors, duplicates, missing values, inconsistent formats, and irrelevant records. Appropriate correction, removal, or documentation makes the remaining data more suitable for analysis and training. Option A is correct. Cleaning does not eliminate all data or allow prediction without data; it improves the quality of useful data.
Which subject and chapter does this question cover?
This is a Class 9 Artificial Intelligence question. Chapter: Data Literacy. Topic: preprocessing.
