Comments (3)
Thanks for making this work open-source.
I have tried to replicate your results using Taiwanese datasets.
I have generated images with dimension size of 50 and a period size of 20.
I have done testing with a random forest classifier.
I have tried a different number of estimators to check the improvement of the result.
I get accuracy around 0.55 with the shared Taiwanese dataset.
I would like to know whether you have a guess about what I could be missing?
I would like to know also why there is such a big gap between my results using the exact same pipeline and the results mentioned in the paper.
Hi, I got a problem just the same.
The accuracy result calculated by deepCNN is also aound 0.55. Do you got the key to increase the accuracy result?
Thank you very much.
from going-deeper-with-convolutional-neural-network-for-stock-market-prediction.
Thanks for making this work open-source.
I've tried different models on the dataset but the accuracy is just overfitting by choosing all up/down. I would like to know whether you have a guess about what I could be missing?
from going-deeper-with-convolutional-neural-network-for-stock-market-prediction.
Thanks for making this work open-source. I have tried to replicate your results using Taiwanese datasets. I have generated images with dimension size of 50 and a period size of 20. I have done testing with a random forest classifier. I have tried a different number of estimators to check the improvement of the result. I get accuracy around 0.55 with the shared Taiwanese dataset. I would like to know whether you have a guess about what I could be missing? I would like to know also why there is such a big gap between my results using the exact same pipeline and the results mentioned in the paper.
I got the same issue here. Have you resolved the issue?
from going-deeper-with-convolutional-neural-network-for-stock-market-prediction.
Related Issues (7)
- The way you create label is different from the description in your master thesis
- fail to convert to images HOT 1
- trying to use it and breaks literally every step of the way HOT 1
- tons of issues with keras2 HOT 1
- Format String F not compatible for python 3.5 HOT 1
- There seems to be a mistake here! HOT 1
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