UCR_Time_Series_Classification_Deep_Learning_Baseline
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cauchyturing
Fully Convlutional Neural Networks for state-of-the-art time series classification
How do the models perform for multivariate time series classification? the commented list in the code only contains univariate time series
May I ask two questions of your FCN code please? 1. Traditional sequential data is of three dimensions: (batch_size, sequence_length, sequence_dimension). Why the data is four dimension in your code?...
great code thanks may you clarify : will it work for multivariate time series prediction both regression and classification 1 where all values are continues values weight height age target...
Hello, I've copied your Adiac data and FCN.py to run with spyder (Python3.7). But it returned a ValueError: Input tensors to a Functional must come from `tf.keras.Input`. Received: 0 (missing...
I have run the code twice and I find that the performance of FCN and Resnet is normal but in MLP the performance is very low. FCN 0.034404267222644426 0.8465473055839539 0.014002826408698009...
Wonderful job! I studied your paper these days. Your paper proposed a strong baseline for time series classification in UCR. From the results of the paper, FCN and ResNet have...
i think the result is too high.
[Time Series Classification from Scratch with Deep Neural Networks: A Strong Baseline] It can be seen from this paper that the author choose the best model that achieves the lowest...
Hi, may I ask what is the value reported as the result? Since you stated that it is Mean Per-Class Error. Is it actually the training loss?
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Fully Convlutional Neural Networks for state-of-the-art time series classification