--The data for wins and horses are as follows. --index is horse number --columns are win odds and single horse odds (eg 1 is horse number 1 single horse odds)
--Output the difference between horse single synthetic odds and win odds ――From here, choose the horse number with the small winning odds and the large difference.
--From the above results, I thought it would be better to use ** horse numbers '1' and '3' **.
model_0## --In model_0, Mamono '3' was used as an argument. -** Minimize the number of bets (100 yen per bet) and set the conditions so that the difference (yen) between the refund (yen) and the total number of bets * 100 (yen) will be positive regardless of which horse wins. did** ――The difference is negative because the condition is met, but the number of bets has been rounded up at the end, so the value has changed. --Solved indicates that this optimization problem has been solved ―― 48.0 shows the total number of bets
model_1## --In model_1, we used single horse '1' and single horse '3' as arguments. -** The condition was set so that the total refund amount is maximized and the difference (yen) between the refund amount (yen) and the total number of bets * 100 (yen) is positive regardless of which horse wins. Also, put the maximum number of bets in the argument and set a condition so that it does not exceed that. (1000 in this article) ** ――In this case, the betting method is concentrated on the place with the highest odds so that the horse with the lowest odds does not lose much.
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