Closed trentmc closed 7 months ago
We recently introduced balance_classes with possible values of SMOTE | RandomOverSampler | None.
balance_classes
SMOTE | RandomOverSampler | None
Weirdly, when it runs in sim_engine for 5000 epochs, it never predicts "up". Weird.
Why is this?
Key datapoint: it only does the weird behavior when balance_classes != None.
5000 logreg AR=1 BTC ETH weight_recent=10x_5x, balance_classes=RandomOverSampler
5000 logreg AR=1 BTC ETH weight_recent=10x_5x, balance_classes=SMOTE
5000 logreg AR=1 BTC ETH
800 svc ar=10 BTC
1000 svc AR=1 BTC ETH max-n-train=100
5000 svc AR=3 BTC ETH ocv n-train=200 weight-recnet calibrate-probs
1000 svc ar=3 BTC ETH max-n-train=100
I just ran this again. It doesn't have this issue anymore; I couldn't reproduce the results from before. It's likely that there was a bug.
Background / motivation
We recently introduced
balance_classes
with possible values ofSMOTE | RandomOverSampler | None
.Weirdly, when it runs in sim_engine for 5000 epochs, it never predicts "up". Weird.
Why is this?
Key datapoint: it only does the weird behavior when balance_classes != None.
Examples without up
5000 logreg AR=1 BTC ETH weight_recent=10x_5x, balance_classes=RandomOverSampler
5000 logreg AR=1 BTC ETH weight_recent=10x_5x, balance_classes=SMOTE
Examples with up
5000 logreg AR=1 BTC ETH
800 svc ar=10 BTC
1000 svc AR=1 BTC ETH max-n-train=100
5000 svc AR=3 BTC ETH ocv n-train=200 weight-recnet calibrate-probs
1000 svc ar=3 BTC ETH max-n-train=100