<p><b>Abstract</b>—We look at a single point in the feature space, two classes, and <tmath>$L$</tmath> classifiers estimating the posterior probability for class <tmath>$\omega_1$</tmath>. Assuming that the estimates are independent and identically distributed (normal or uniform), we give formulas for the classification error for the following fusion methods: average, minimum, maximum, median, majority vote, and oracle.</p>