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paifu analyze demo: infer ranking based on score #22
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A naive implementation: then output |
To measure how confident we estimate possibility by When the Here's some possible solution:
Some data structure support fast fallback is also needed. |
Using SVM as baseline of classification. As you well know, SVM(SVC) is a widely used classifier that is robust and interpretable. Thus it might be a possible baseline of this question. I've trained 8 models with different train_set_size(50000, 100000), different multi-classifier (OveVSOne and OneVsRest) and different kernel(rbf, linear) and tested on five test sets, each contains 300000 records. All sets are picked randomly and uniquely from tenhou records, which have 57755880 items. 19 characters are used, which are Result are listed below,
And the raw data:
Since SVM is not so suitable for multi-classification and can not give the probability directly, I then tried RVM, which uses Bayesian Inference that can solve these problems. However, the train time and resource requirements of RVM is much more larger. Thus I only able to train one with the train_set_size of 5000 and the accuracy is only 25%. |
Something like:
Given current score, game round, is oya, seat order, output ranking possibility like:
means that you may most probably get third ranking, and almost safe from being last, and has substantial chance to beat second player down, from given situations. Tenhou Pt estimation is also possible.
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