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rosdyana / Going-Deeper-with-Convolutional-Neural-Network-for-Stock-Market-Prediction

Repository for Going Deeper with Convolutional Neural Network for Stock Market Prediction
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RandomForest Classifier results #5

Open Mirmix opened 4 years ago

Mirmix commented 4 years ago

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.

nkchem09 commented 3 years ago

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.

yc-wang00 commented 2 years ago

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?

yc-wang00 commented 2 years ago

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?