Hirotugu Akaike

Hirotugu Akaike was a Japanese statistician best known for developing the Akaike Information Criterion (AIC). AIC is a tool used by researchers to compare statistical models and select the one that best balances accuracy and simplicity. It helps prevent overfitting, where a model fits the data too closely and performs poorly on new data. Essentially, Akaike's contribution provides a practical way to choose models that explain data well without being overly complex, aiding in more reliable predictions and insights across various scientific fields.