The Impact of Data Annotation Quality on the Accuracy of Machine Learning Models
“Data annotation quality influences the accuracy of the machine in a significant way. With the help of learning models, it directly affects the reliability and correctness of the labeled data. It is mostly used for training, validation, and testing.”
– Mr. Dylan E. Curry, Machine Learning Expert
Problem
The challenges with the impact of data annotation quality is a big question today. It goes hand in hand with machine learning model accuracy and performance.
Solution
The problem can be solved with Investigating the impact of varied data annotation quality. It would help if you did not forget to analyze the expertise of the annotator about the model performance.
Results
It improves the accuracy model, while incorrect annotations hinder performance.
Bottom Line Impact
95,000
Data Annotated
Increased
accuracy of machine learning models
Benefits
Costs and timings of the annotation processes are decreased
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