All Questions
73 questions
8
votes
2
answers
304
views
How to design a neural network that gets the author name of a piece of art as input?
I'm building a neural net to predict the value of a piece of art with a wide range of inputs (size, art medium, etc.) and I would like to include the author as an input as well (it is often a huge ...
- 81
7
votes
2
answers
455
views
How can a neural network distinguish a rotated 6 and 9 digits?
Rotated MNIST is a popular dataset for benchmarking models equivariant to rotations on $\mathbb{R}^2$, described by $SO(2)$ group or its discrete subgroups like $\mathbb{Z}^{n}$:
Group equivariant ...
- 2,754
6
votes
1
answer
505
views
How to add more features to the input of a machine learning algorithm?
I am trying to perform a binary classification of tweets using machine learning.
The usual way of doing this seems to be putting a hand-classified tweet's words into a big vector, then use that ...
- 237
5
votes
1
answer
2k
views
What is "conditioning" on a feature?
On page 98 of Jet Substructure at the Large Hadron Collider: A Review of Recent Advances in Theory and Machine Learning the author writes;
Redacted phase space: Studying the distribution of inputs ...
- 153
5
votes
1
answer
2k
views
How to handle varying types and length of inputs in a feedforward neural network?
After learning the basics of neural networks and coding one working with the MNIST dataset, I wanted to go to the next step by making one which is able to play a game. I wanted to make it work on a ...
- 53
5
votes
0
answers
69
views
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
4
votes
3
answers
1k
views
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
4
votes
1
answer
7k
views
What are bag-of-features in computer vision?
In computer vision, what are bag-of-features (also known as bag-of-visual-words)? How do they work? What can they be used for? How are they related to the bag-of-words model in NLP?
- 41.4k
4
votes
2
answers
60
views
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
4
votes
1
answer
76
views
When working with time-series data, is it wrong to use different time-steps for the features and target?
When working with time-series data, is it wrong to use daily prices as features and the price after 3 days as the target?
Or should I use the next-day price as a target, and, after training, predict 3 ...
- 41
3
votes
2
answers
122
views
How do we know that the neurons of an artificial neural network start by learning small features?
I'd like to ask you how do we know that neural networks start by learning small, basic features or "parts" of the data and then use them to build up more complex features as we go through ...
- 573
3
votes
1
answer
77
views
How are small scale features represented in an Inverse Graphics Network (autoencoder)?
This post refers to Fig. 1 of a paper by Microsoft on their Deep Convolutional Inverse Graphics Network:
https://www.microsoft.com/en-us/research/wp-content/uploads/2016/11/kwkt_nips2015.pdf
Having ...
- 161
3
votes
1
answer
83
views
Do the eigenvectors represent the original features?
I've got a test dataset with 4 features and the PCA produces a set of 4 eigenvectors, e.g.,
...
- 131
2
votes
2
answers
411
views
How to convert color information to 1D feature vector?
We are making a classification model that takes a clip of a movie as an input and predicts who the director is. Roughly speaking, it will be a model that understands film directors' unique style.
We ...
2
votes
2
answers
5k
views
What is the difference between features and inputs in machine learning?
I have seen many places that features and inputs have been used interchangeably when talking about machine learning especially deep neural networks. I want to know if they are indeed the same thing or ...
- 145
2
votes
1
answer
562
views
Does the correlation between inputs affect the model performance?
I'm currently working on a regression problem and I have 10 inputs/attributes.
What should I do if there are correlations between different features of the input data? Does the correlation between ...
- 133
2
votes
2
answers
55
views
What is the sensitivity of coefficients in multicollinearity?
I've heard that the coefficients in multicollinearity are very sensitive, and can change due to small changes in the data.... Isn't it a problem with the dataset itself that we have different data? ...
- 23
2
votes
1
answer
695
views
How to calculate a meaningful distance between multidimensional tensors
TLDR: given two tensors $t_1$ and $t_2$, both with shape $(c,h,w),$ how shall the distance between them be measured?
More Info: I'm working on a project in which I'm trying to distinguish between an ...
- 371
2
votes
1
answer
439
views
Is it true that channels always represent colours of an image?
Convolutional neural networks are widely used in image-related tasks in artificial intelligence.
The input of a conventional neural network is generally an image. The output of a convolutional neural ...
- 3,990
2
votes
2
answers
152
views
Can we train the model to detect real users with only positive labels?
We have hundreds of thousands of customers records, and we need to take the benefits of our data to train a model that will recognize fake entries or unrealistic ones for our platform, where customers ...
- 121
2
votes
1
answer
328
views
If I wanted to calculate multiple feature maps in a convolutional layer, should the filters be trained individually?
Assume I have an input of size $32 \times 32 \times 3$ and pass it to a convolution layer. Now, if my kernel size were to be $5 \times 5 \times 3$ and the depth of my convolution layer were to be 1, ...
- 158
2
votes
1
answer
69
views
Does the weight vector form imply feature space curvature?
I came across this sentence when exploring a simple nearest neighbor classifier method using Euclidean distance (link):
The slightly odd thing about using the Euclidean distance to compare features ...
- 21
2
votes
2
answers
687
views
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
2
votes
2
answers
466
views
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 ...
- 177
2
votes
1
answer
2k
views
What are examples of node 'features' in graph networks?
Context: I was reading Chapter 3 in the following book (here) about graph representation learning. Before I get to node embeddings, I wanted to make sure that I do understand what is meant by the ...
- 165
2
votes
0
answers
936
views
What does it mean by "low-level" and "high-level" in features generated by CNN?
Across the literature, the terms "high-level" and "low-level" are generally used as an adjective to the features generated by the convolution neural network as intermediate ...
- 3,990
2
votes
0
answers
90
views
Does coarse coding with radial basis function generate fewer features?
I am learning about discretization of the state space when applying reinforcement learning to continuous state space. In this video the instructor, at 2:02, the instructor says that one benefit of ...
- 181
1
vote
1
answer
171
views
Is there any advantage to providing multi-dimensional input to torch modules?
Most layer types in torch.nn such as torch.nn.Linear accept input with more than one dimension. Is there any advantage in doing so if you can shape your data to represent a certain arrangement in ...
- 13
1
vote
1
answer
77
views
Features for a Content-Based recommendation system
I'm working on a hybrid recommendation system (collaborative and content-based) for an online ordering/shopping app. So far I've managed to identify a data-source for the collaborative model (likely ...
- 11
1
vote
1
answer
439
views
Can I always interpret features as random variables in machine learning safely?
Consider the following statements from Chapter 5: Machine Learning Basics from the book titled Deep Learning (by Aaron Courville et al.)
Machine learning tasks are usually described in terms of how ...
- 3,990
1
vote
1
answer
53
views
Does feature scaling have any benefits if all features are on the same scale?
By scaling features, we can prevent one feature from dominating the decisions of a model. For example, say heights (cm), and age (years) are two features in my data. Since range of heights is larger ...
- 1,040
1
vote
1
answer
101
views
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 ...
- 23
1
vote
2
answers
65
views
Feature scaling strategy for many feature with very large variation between them?
I was running into a situation in which my input feature experience a very large variation in term of magnitude.
Particularly, consider feature 1 belong to group 1 and feature 2 3 4 belong to group 2,
...
1
vote
1
answer
5k
views
What is a temporal feature?
What is a temporal feature, what features make something temporal in nature? Is this problem agnostic? How does it change from different fields of study?
- 71
1
vote
2
answers
250
views
Which neuron represents which part of the input?
In a neural network, each neuron represents some part of the input. For example, in the case of a MNIST digit, consider the stem of the number 9. Each neuron in the NN represents some part of this ...
- 111
1
vote
1
answer
77
views
Regression model is doing exceptionally very well on time series
I have the following task to do: I have time series data. Training by the consecutive 3 days to predict the each 4th day. Each day data represents one CSV file which has dimension 24x25. Every ...
- 113
1
vote
1
answer
126
views
Feature vector representation of probability distribution
I have a series of multiple probability distribution like this:
[
[0.2, 0.3, 0.5],
[0.1, 0.2, 0.7],
...
]
Do you have any suggestions how I can represent this ...
- 43
1
vote
1
answer
747
views
What kind of features does each node have as an input graph to a graph neural network?
What kind of features does each node have as an input graph to a graph neural network? For example, we want to do image classification with GNN, what are the features of each pixel? Or if anyone could ...
- 11
1
vote
1
answer
60
views
What is the name of a feature space which has consistant distance-related properties?
What is the word describing a feature space where distance between two elements has a decisive informational value, whatever the pair of elements is?
For example if a model creates embeddings for ...
- 11
1
vote
1
answer
421
views
When is it appropriate to use information like sex or race in ethical machine learning?
I'm a little confused on best practices regarding ethical ML. Specifically, I've seen in some courses that when building a model that affects people, it's helpful to have sensitive personal ...
- 113
1
vote
1
answer
96
views
How to predict the best from a set of messages - best practice
Suppose I have a set of messages A,B,C,D and I want to produce the best message for a website user at a given time.
For training I plan to show random users a random single message [A/B/C/D] and fill ...
- 11
1
vote
1
answer
71
views
When doing binary classification with neural networks, how can I order the importance of the features for a class?
I have a simple neural network for binary classification.
The input features include age, sex, economic situation, illness, disability, etc. The output is simply 1 and 0.
I would like to order the ...
- 111
1
vote
1
answer
511
views
How can $\nabla \hat{v}\left(S_{t}, \mathbf{w}_{t}\right)$ be 1 for $S_{t}$ 's group's component and 0 for the other components?
In Sutton's RL:An introduction 2nd edition it says the following(page 203):
State aggregation is a simple form of generalizing function approximation in which states are grouped together, with one ...
- 797
1
vote
0
answers
73
views
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
1
vote
0
answers
87
views
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 ...
- 11
1
vote
1
answer
90
views
Transfer Learning for Solar Energy Production Forecasting with LSTM: Generalized vs. Specialized Models
I am working on a solar energy production forecasting problem using LSTM multi-step models to predict 1/4/8h ahead of solar energy production for different solar installations. Our goal is to help ...
1
vote
0
answers
119
views
Understanding the features given in Example 13.1 of Sutton and Barto
I'm struggling to understand the notation used to represent the features within Example 13.1 (Short corridor with switched actions" in the Sutton and Barto RL book.
I assume as it is a free pdf ...
- 111
1
vote
0
answers
41
views
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
1
vote
1
answer
313
views
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 ...
- 23
1
vote
0
answers
90
views
What do state features mean in the context of inverse RL?
I am reading Zeibart's Inverse RL paper, and it states -
The agent is assumed to be attempting to optimize some function that linearly maps the features of each state, $f_{sj} \in \mathbb{R}^k$, to a ...
- 670