Overfitting vs Underfitting คำที่ว่าด้วยปัญหาจากความซับซ้อนของข้อมูล

These two factors correspond to the two central challenges in machine learning: underfitting and overfitting Underfitting is when the training

Model overfitting is a notion that arises when the model learns too well the training data An ML algorithm is underfitting when it cannot capture the

overfitting 10 techniques to avoid overfitting · Train with more data · Data augmentation · Addition of noise to the input data · Feature selection · Cross-

overfitting The performance can be measured using the percentage of accuracy observed in both data sets to conclude on the presence of overfitting If the model performs