キャリブレーションプロット
A calibration plot, also known as a reliability diagram, is a graphical representation used to evaluate how well the predicted probabilities from a statistical model align with the actual outcomes. This is particularly important in fields like 機械学習 and statistics, where models often provide 予測.
一般的なキャリブレーションプロットでは、x軸は予測確率（しばしば区間に分けられる）を表し、y軸は実際に観測された結果の頻度を示します。例えば、モデルがある事象が発生する確率を70％と予測した場合、キャリブレーションプロットは、その予測が実際にどれだけ頻繁に起こるかを示します。
A perfectly calibrated model would result in a calibration plot where the predicted probabilities match the actual outcomes, forming a 45-degree diagonal line (often referred to as the ‘calibration line’). If the plot falls above this line, it indicates that the model is under-confident (predicting lower probabilities than observed). Conversely, if it falls below, the model is over-confident (predicting higher probabilities than observed).
キャリブレーションプロットは、モデルを評価するために重要です 二値分類タスク, such as in healthcare for predicting disease presence or in finance for クレジットスコアリング. By visually inspecting the calibration plot, practitioners can make informed decisions about model adjustments, threshold settings, and overall reliability of the predictions.