func updateMatch(lr *lr.LogisticRegression, records []creditRecord, protos []*hector.Sample, match [][]float64) {
predictions := make([]float64, len(protos))
for i, proto := range protos {
predictions[i] = lr.Predict(proto)
}
for borrower, dist := range match {
r := records[borrower].returned
nr := records[borrower].borrowed - r
for iuser, gamma := range dist {
match[borrower][iuser] = gamma *
math.Exp(float64(r)*math.Log(1-predictions[iuser])+float64(nr)*math.Log(predictions[iuser]))
}
norm := sum(match[borrower])
for iuser, prob := range match[borrower] {
match[borrower][iuser] = prob / norm
}
}
}
