Closed linjianfeng closed 1 year ago
I apologize for the problems you encountered with the Ford StayAlert dataset documentation and code. I appreciate you bringing this issue to our attention. I have made the necessary updates to the code, and I kindly request that you re-download it (or please replace the existing util.py file in your project with the updated version)
Ford dataset: Access the dataset from the following Kaggle competition link: https://www.kaggle.com/competitions/stayalert/data. Download the "stayalert.zip", which contains the following files: Solution.csv fordTrain.csv fordTest.csv
Labeling the test data: The file fordTest.csv does not have labels. To assign labels to the test data, follow these steps: Open the Solution.csv file. Copy the contents of the prediction columns. Paste the copied prediction values into the "ISAlert" column of the fordTest.csv file. Renaming and copying files:
Rename the fordTrain.csv and fordTest.csv files to FordChallenge_Train.csv and FordChallenge_Test.csv, respectively. Copy the FordChallenge_Train.csv and FordChallenge_Test.csv files to the following directory: Datasets/Segmentation/FordChallenge. Column renaming:
Open the FordChallenge_Train.csv and FordChallenge_Test.csv files. Rename the following columns: "TrialID" to "series" "obsNum" to "timestamp" "IsAlert" to "label"
Finally: Copy the FordChallenge_TEST.csv and FordChallenge_Train.csv to: Datasets/Segmentation/FordChallenge
I downloaded Ford StayAlert challenge data according to https://github.com/Navidfoumani/ConvTran/blob/main/Dataset/Segmentation/Segmentation.Txt. The test csv file looks like
There are some problems related to this dataset:
So do you have another version of Ford dataset? And if the algorithm got good score with the ill aligned dataset, maybe it could achieve better performance with rectified code?