Machine Learning, Data Science, Overfitting, Underfitting.
right. low bias, high variance — overfitting — the algorithm outputs very different predictions for similar data. high bias, low variance — underfitting — the algorithm outputs similar predictions for similar data, but predictions are wrong (algorithm “miss”). high bias, high variance — very bad