Alexandra Twin has 15+ years of experience as an editor and writer, covering financial news for public and private companies. Investopedia / Zoe Hansen Overfitting is ...

Model fit can be assessed using the difference between the model's predictions and new data (prediction error—our focus this month) or between the estimated and ...

Ernie Smith is a former contributor to BizTech, an old-school blogger who specializes in side projects, and a tech history nut who researches vintage operating systems for fun. In data analysis, it is ...

Overfitting in ML is when a model learns training data too well, failing on new data. Investors should avoid overfitting as it mirrors risks of betting on past stock performances. Techniques like ...