All Questions
73 questions
2
votes
1
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2k
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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 ...
CommunityBot
- 1
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 ...
- 5,507
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? ...
- 5,507
0
votes
2
answers
26
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What the difference between influence and dependence?
I'll give an example on height and weight. Weight and height are correlated, but it's not necessarily the case that a tall person weighs more or that someone who weighs more is a tall person - and ...
- 23
1
vote
1
answer
90
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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 ...
CommunityBot
- 1
0
votes
0
answers
19
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I developed a fairly simple custom feature selection method for a problem I had. Does it already exist?
I had a specific problem where I had a leave-one-subject-out cross-validation scheme that was a little complex in terms of scoring.
Specifically, I had 21 subjects, and for each subject I had between ...
0
votes
0
answers
11
views
How do I represent the relationship between time and brightness in a machine learning model?
I have done all the feature engineering and am ready to start making a machine learning model that predicts the type of variable star based on its light curve. I have broken down this light curve into ...
- 101
0
votes
1
answer
50
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Is a linear regression model able to figure out the relation of division among two features?
I have a dataset that consists of data about students. The features are things such as passed credits, failed credits, ...
- 166
0
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0
answers
21
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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 ...
0
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0
answers
45
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What does a feature's integrated gradient actually represent in the context of a regression task?
I've been reading about IGs, but all the articles I've read describe it in terms of a classification task. And in that context it makes a little more sense to me as the change in probability for a ...
0
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0
answers
10
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How do nonlinear relationships affect casuality determination
Let's assume that I have only one independent variable and one dependent, and
I have a great model with minimal error which deals well with predicting.
Let's also assume that I do no know the true ...
- 303
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 ...
- 101
0
votes
2
answers
43
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Non constant Feature Importance
I have a financial dataset which has 10 years worth of data. The aim is to build a regressor capable of predicting next year sales. So, if I want to predict sales for 2024, I could use data from 2023, ...
- 101
1
vote
0
answers
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
0
votes
1
answer
50
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Machine Learning Algorithm for identifying the factors contributing to academic performance of students
I have a dataset with several qualitative and quantitative attributes, including age, location (longitude, latitude), city, parent occupation, family size, GPA etc. My task is to find the attributes/...
- 41.4k
0
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0
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20
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Predict outputs based on a variable subset of inputs
To simplify this: I have 5 columns in my dataset -> A, B, C, D and E. I want the neural network to predict the rest of the outputs based on a subset of inputs.
For example:
Case #1
Inputs -> (A) ...
- 1
0
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0
answers
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
1
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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
0
votes
0
answers
39
views
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 ...
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 ...
- 660
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,
...
CommunityBot
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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 ...
- 1,748
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 ...
- 206
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 ...
- 10.5k
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 ...
CommunityBot
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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 ...
CommunityBot
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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 ...
- 632
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 ...
- 1,134
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
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. ...
CommunityBot
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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 ...
- 5,428
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 ...
- 41.4k
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 ...
- 259
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 ...
CommunityBot
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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 ...
- 41.4k
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
0
votes
0
answers
51
views
Does it make sense to compare images (samples) with words (features)?
Consider the following paragraphs from the introduction of the chapter named Recurrent Neural Networks from the textbook titled Dive into Deep Learning
So far we encountered two types of data: ...
- 41.4k
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 ...
- 539
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 ...
- 41.4k
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 ...
CommunityBot
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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
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1
answer
1k
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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 ...
- 41.4k
1
vote
1
answer
439
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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
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 ...
- 41.4k
1
vote
0
answers
34
views
What is the difference between the $Q_a$ calculated to update delta and those to select next action in the exploitation phase?
As the title suggests, I have a doubt about the computation of the $Q_a$ used to update the delta and the $Q_a$ used to select the next action in the exploitation phase, as shown below (source of ...
- 41.4k
5
votes
1
answer
2k
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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 ...
- 41.4k
0
votes
1
answer
1k
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How to find "relationships" between two data representations?
I am a researcher in a field, and new to the whole of AI and machine learning techniques. May the following question is trivial or not framed in the ML language but I try my best.
I have two sets of ...
CommunityBot
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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 ...
CommunityBot
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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, ...
- 41.4k