Comments (3)
dnguyengithub
commented on August 16, 2024
1
Hi,
The validation set serves 2 purposes:
- To prevent overfitting (by comparing the average log likelihood on the training set and on the validation set)
- To calculate the distribution in each small cell, which will be used in the local thresholding step of the a contrario detection. Please see Section III-C of this paper https://arxiv.org/pdf/1912.00682.pdf for details.
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RobertSellers
commented on August 16, 2024
I appreciate the feedback. Thank you.
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muzunpostalci
commented on August 16, 2024
Hello @dnguyengithub ,
Can you further elaborate on why the validation set is used to calculate the distribution? I observed that the a contrario detection is dependent on the distribution of each cell but I didn't get why the validation set is a good candidate for it. Does using training set for this matter lead to overfitting?
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Related Issues (20)
- VRNN Model HOT 1
- contrario detection Issues HOT 3
- Ship type HOT 5
- Using my own dataset. HOT 15
- Dataset Details HOT 3
- Logits Vs Probs. Are they being mixed up? HOT 2
- Using new dataset HOT 9
- 4 hot vector with dataset HOT 1
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- Environment setup difficulties HOT 5
- GPU Power required to run GeoTrackNet HOT 2
- Suitable Cuda and Graphic card used with environment?
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- ValueError while training the embedding layer HOT 7
- ValueError: ./chkpt/elbo-ct_2017010203_10_20_train.pkl-data_dim-702-latent_size-100-batch_size-1 doesnt exist.
- Inputs for csv2pkl.py HOT 2
- LAT_MIN, LAT_MAX, LON_MIN, LON_MAX Values HOT 1
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