"Directed, Fit: Fix the calculation of p-rule when the cardinality of the DV is greater than 2.
Explanation & Algorithm: Right now, p-rule is the p-value from comparing q(DV|IV), the calculated conditional probability distribution of the DV, given the IV state, with a uniform distribution. For |DV|=2 this is fine, but for |DV|>2, it actually isn't adequate. The new algorithm does this comparison with a uniform distribution as a first step, but if the p-value < p-cutoff, and it thus passes this first test, it then does a second test which compares the two highest q(DV|IV) values with (.5, .5), after first normalizing these two highest values so that they sum to 1. Call the p-value for the first test p-value1 and the p-value for the second test p-value2. If the first test fails, Occam should report p-value1. If the first test passes, then report p-value2. Indicate somehow (e.g., with some special character after the p-value) which p-value is being reported."
"Directed, Fit: Fix the calculation of p-rule when the cardinality of the DV is greater than 2. Explanation & Algorithm: Right now, p-rule is the p-value from comparing q(DV|IV), the calculated conditional probability distribution of the DV, given the IV state, with a uniform distribution. For |DV|=2 this is fine, but for |DV|>2, it actually isn't adequate. The new algorithm does this comparison with a uniform distribution as a first step, but if the p-value < p-cutoff, and it thus passes this first test, it then does a second test which compares the two highest q(DV|IV) values with (.5, .5), after first normalizing these two highest values so that they sum to 1. Call the p-value for the first test p-value1 and the p-value for the second test p-value2. If the first test fails, Occam should report p-value1. If the first test passes, then report p-value2. Indicate somehow (e.g., with some special character after the p-value) which p-value is being reported."