All Questions
Tagged with features deep-learning
15 questions
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Deep Learning: Architecture vs. Features for Performance?
In deep learning, when aiming for peak metric performance, is a well-designed architecture with imperfect features/dataset generally preferable to a poorly designed architecture with high-quality ...
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73
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Compare two songs content using Audio Spectogram Transformer
I'm trying to establish a similarity metric between two songs. To do this I'm using the AST model on HuggingFace. This model basically works in a way very similar to a ViT but applied to spectograms ...
- 111
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11
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Finding invariant feature areas within representation vector for each meta-class/group?
I have pairs of images which are not the same class, but are from the same meta-class/group. I have a standard CNN which produces a representation for each sample.
If I have several pairs of images ...
- 11
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87
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What is the best way to train a neural network with a variable number of inputs?
Suppose I have a neural network with 5 inputs: [A,B,C,D,E]
There is only 1 output. The expected accuracy of the model should increase when all 5 inputs are ...
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39
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Calculating class-specific permutation feature importances for multilabel classification problem
I would like to apply the permutation feature importance technique to rank the features of a siamese network model that I trained. I am currently using this siamese network to perform some kind of ...
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41
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Why "Good Model" that performs great on holdout validation data fails on production data
I have this binary regression model that has ~500 futures with an unbalanced dataset with the following results.
...
- 23
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313
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How to handle out-of-bound values in Production data?
So I have this model but the data may vary. And it is virtually impossible to always have the values in bounds. If I do I`d have to use larger period leading to concept shift which is worse.
The ...
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4
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2
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60
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Is there any proper literature on the types of features that different layers of a deep neural network learn?
Let's consider a deep convolutional network. It seems that there is some consensus on the following notions:
1. Shallow layers tend to recognise more low-level features such as edges and curves.
2. ...
- 141
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1
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When can we call a feature "hierarchical"?
Features in machine learning are the attributes of the elements of a data set. They are considered as random variables in probability.
Consider the following excerpt from 1.1: The deep learning ...
- 3,990
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3
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When is it necessary to manually extract features to feed into the neural network rather than providing raw data?
Usually, Neural Networks uses raw data. You do not need to extract features manually. NN's can find & extract good features which is a pattern of an image, signal or any kind of data. When we ...
- 257
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1
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687
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What is the impact of the number of features on the prediction power of a neural network?
What is the impact of the number of features on the prediction power of an ANN model (in general)? Does an increase in the number of features mean a more powerful prediction model (for approximation ...
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1
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101
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When is adding a feature useless?
I'm building a model, where, from a feature set A, I want to predict a target set C. I need to understand if another feature set B, together with A, can improve my model performances, instead of using ...
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69
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Training and inference for highly-context-sensitive information
What is the best way to train / do inference when the context matters highly as to what the inferred result should be?
For example in the image below all people are standing upright, but because of ...
- 101
2
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2
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687
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Is the number of feature maps equal to the number of kernels in the LeNet 5 architecture?
In LeNet 5's first layer, the number of feature maps is equal to the number of kernels. However, the second convolutional layer has a depth different from the 3rd layer. Does the filter size dictate ...
- 317
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2
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466
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How do neural networks weigh multiple inputs/features of different dimensionality?
I am confused about how neural networks weigh different features or inputs.
Consider this example. I have 3 features/inputs: an image, a dollar amount, and a rating. However, since one feature is an ...
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