All Questions
Tagged with neural-network deep-learning
1,433
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How weight vector behave when we initialize the weight to 0 in case of perceptron
While reading in book i encountered this statement
Now, the reason we don't initialize the weights to zero is that the learning rate (eta) only has an effect on the classification outcome if the ...
- 101
1
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1
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Everything is classified as background by segmentation model
I am training a U-NET model for medical image segmentation. Problem is that the binary masks that im using to train the model mostly consist of background pixels and a very small region of the whole ...
- 61
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14
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How to increase the optimial cutoff point(youden index) after training a model?
So I trained a model based on a medical dataset and and I got an AUROC for detecting cancer in brain images as about 0.96 and i noticed that the youden index is 0.1 but i want to increase it to 0.5 , ...
-1
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1
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WGAN generating images from the training data
Is it possible for gan to remember somehow training data distribution?
Or maybe somеthing leaks out when I calculate gradients?
...
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What is the "fast version" of ZFNet referenced in SPPNet and Faster R-CNN papers?
I'm reading old papers:
SPPNet: Link
Faster R-CNN: Link
In both cases, the authors refer to a "fast version of Zeiler and Fergus (ZF) Net"; specifically:
In SPPNet:
ZF-5: this ...
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46
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Why can't I replicate the results from this paper?
I'm trying to train a model to evaluate chess positions, following the methodology from this paper (note that the author presents several different architectures, but I'm only looking at the ANN with ...
1
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1
answer
55
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wierd neural network approache
I'm working on a problem where I need to create a neural network to optimize the seating arrangement for 24 unique individuals in a 6x4 grid, minimizing conflicts between adjacent (up,down,left,right) ...
- 101
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1
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34
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Predicted output is only 0s
I am developing a neural network using Home credit Default Risk Dataset.
The prediction should be between 0.0 and 1.0 but my algorithm's outcome is just 0.0 for every row.
My Code
...
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Semantics Building In LSTM-Based Models - How does a LSTM is able to extract and represent long data using just one value (long-memory)
How does a LSTM is able to extract and represent long sequences with data while using just one value (long-memory / LM) to maintain all this information?
If multiple value were used, it could be ...
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1
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27
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How to update first layer weights?
I’m trying to make a neural network without using any deep learning library that recognizes numbers in the mnist database. Its structure is: 784 input neurons (for the 784 pixels in the number images),...
3
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1
answer
45
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Is it legal to use a model found on github for a personal project and uploading the personal project onto github? [closed]
I found a great model I would like to use and make improvements upon for a personal project. It doesn't contain any liscenses nor does it mention anything about restrictions of use.
Are AI models like ...
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Theoretical Limitations of Achieving 100% Accuracy in Modeling Non-linear Relationships with Neural Networks
I am working on a project where I need to model a specific non-linear relationship using a neural network. The relationship is given by $y = 3x_1^2x_2^3 $. The approach involves:
Preprocessing the ...
1
vote
1
answer
62
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Improving GPU Utilization in LLM Inference System
I´m trying to build a distributed LLM inference platform with Huggingface support. The implementation involves utilizing Python for model processing and Java for interfacing with external systems. ...
- 111
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1
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Accuracy and test_accuracy gives a result =1
I've developed a code for classifying hyperspectral images using three different convolutional neural network (CNN) architectures: 1D, 2D, and 3D. The code has two main parts:
Preprocessing and data ...
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1
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57
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Is it possible to train a neural network to feed into a Random Forest Classifier or any other type of classifier like XGBoost or Decision Tree?
I want to create a model architecture to predict future stock price movement as such:
The Goal of this model is to predict if the price will go UP or DOWN within the next 3 months.
I have tried a few ...
- 1