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Technical concepts
A statistical measure of overlap between two probability distributions. Concord by IaxaI uses the related Bhattacharyya coefficient to score how much two entities could plausibly be the same.
Definition
The Bhattacharyya coefficient measures overlap between two probability distributions; it is the integral of the geometric mean of the two density functions over their shared support, bounded between 0 and 1. The Bhattacharyya distance is the negative log of that coefficient. Two distributions with identical support score a coefficient of 1; two with disjoint support score 0. The metric is symmetric and respects similar shape rather than just mean separation, which makes it useful when the two values being compared are noisy or expressed as ranges. Concord by IaxaI's entity resolution engine treats every comparison as a comparison of distributions, not point values. An IP address carries a subnet tolerance. A timestamp carries a window. A username carries name-component plus Soundex variants. The Bhattacharyya coefficient between the two distributions is the raw overlap signal. Temperature scaling turns it into a probability. Conformal prediction turns it into a coverage-guaranteed set.
See also
Calibrated Identity
Entity resolution with a coverage-guaranteed prediction set. Concord tells you when it doesn't know, instead of guessing.
Conformal Prediction
A distribution-free statistical wrapper that gives any predictor a coverage-guaranteed prediction set. Useful for honest "I don't know" outputs.
Sentence Transformer Embeddings
Dense vectors that turn text into geometry, used for translation alignment, entity resolution, and knowledge-graph retrieval.
Maximum Mean Discrepancy (MMD)
A kernel-based two-sample test for whether two batches of data come from the same distribution. The drift detector's primary statistic.
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