Each of the computed indices (𝐼 * + " , 𝐼 * + & , 𝐼 * + % ) take values between 0 and 1. Let 𝜏 ? , between 0 and 1, be the decision thresholds for a given index 𝐼 ? . That is, when 𝐼 ? > 𝜏 ? , we assume the predicted molecular mass 𝛾 is the true molecular mass of the analyte, and when 𝐼 ? ≤ 𝜏 ? , we assume the predicted 𝛾 is incorrect. For a given 𝜏 ? and set of test data, we can generate a contingency table, commonly known as a confusion or error matrix, that summarizes how well the classifier threshold performs under tested circumstances,