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Why might a neural network consistently underestimate its target?

It seems like you are dealing with a zero inflated lognormal (ZILN) distributed target. In this case standard error loss / metrics are not correctly capturing the error structure. I suggest to take ...
Georg M. Goerg's user avatar
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Using TensorFlow with Intel GPU

Try Intel extension for Tensorflow https://intel.github.io/intel-extension-for-tensorflow/latest/docs/install/install_for_xpu.html#
Anisha's user avatar
  • 1
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What is the relationship between the accuracy and the loss in deep learning?

Ayúdenme a aclarar esta duda por favor Después de ver este comentario: ------si sus datos están entre 0 y 1, una pérdida de 0,5 es enorme, pero si sus datos están entre 0 y 255, un error de 0,5 es ...
jhazmin tapia's user avatar
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Classifying with certainty

You can easily quantify uncertainty for all these problems using Conformal Prediction. https://github.com/valeman/awesome-conformal-prediction
valeman's user avatar
  • 11
0 votes

Video segmentation vs image segmentation

Brian is right. You need to consider a video as a bunch of concatenated images. 30 FPS (Frame Per Second) video has 30 frames on every second of it. You run your model (segmentation, detection, ...
spawnfile's user avatar
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How to get probabilities values with keras?

To get probabilities, you have to use something like this: probabilities = tf.nn.softmax(prediction_results).numpy()
Vladimir S.'s user avatar
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Classification task on boolean only features: what model/layers/activators are better?

As you have a lot of labels to predict. I will suggest few basic things which might improve the score or will improve the interpretability: ...
Harshad Patil's user avatar
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Classification task on boolean only features: what model/layers/activators are better?

Most architecture rely on float operations as the optimisation process requires to work with a continum of values. If you want to solve for parameters than can only take discrete values, then it's not ...
Lelouch's user avatar
  • 131
0 votes

CNN model with images - 100% accuracy on validation and test sets with limited data?

Taking 207 images made from 7 videos, and then randomly forming train and validation sets can lead to a massive data leakage: both train and validation sets will have many images from every video. For ...
Valentas's user avatar
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How do I create an Image Dataset for a CNN?

You should restructure your Imagefile folder based on your CSV file. You can write some code to create subfolder based on your CSV file, and move your images to relevant subfolder. os.makedirs() then ...
Yong Lee's user avatar
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Keras single sample prediction returns different values

I do not how to fix this in a correct manner, but it seems the reason is because the model was trained on batches rather than individual examples. My model is also based on ResNet50 (a part of it) and ...
Neco's user avatar
  • 101
0 votes

Custom Loss Function in Tensorflow for UNet

From the docs the gather function requires int32 or int64 indices, while you seem to provide ...
Luca Anzalone's user avatar

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