What is Overfitting in Machine Learning?

overfitting  Overfitting is a modeling error which occurs when a function is too closely fit to a limited set of data points It is the result of an overly Overfitting is a problem where a machine learning model fits precisely against its training data Overfitting occurs when the statistical model

Underfitting หรือ อาจจะเรียกอีกอย่างว่า โมเดลมี high bias ส่วนวิธีการทางคณิตศาสตร์ในการปรับโมเดล ป้องกันปัญหา Overfitting นั้นมีชื่อเรียกว่า regularization ซึ่งจะให้ผลลัพธ์คือปรับค่าน้ำหนัก Kaggle competitions are a particularly well-suited environment for studying overfitting since data sources are diverse, contestants use a wide range of model

When an ML model aces the training data—spotting patterns and trends—but is unsuccessful when presented with new data, overfitting occurs, which Overfitting occurs when our model becomes really good at being able to classify or predict on data that was included in the training set, but is