All Questions
Tagged with regressors or features
22 questions with no upvoted or accepted answers
5
votes
0
answers
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
votes
1
answer
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 ...
- 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
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
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
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 ...
1
vote
0
answers
311
views
How to train a machine learning model with multiple attributes and one target value?
I'm working on a machine learning problem where I need to guess which customers will churn and which of them will continue to be customers.
I have $X_0, X_1, X_2, X_3, X_4, X_5$ and $X_6$ attributes ...
1
vote
0
answers
104
views
How can I use gradient boosting with multiple features?
I'm trying to use gradient boosting and I'm using sklearn's GradientBoostingClassifier class.
My problem is that I'm having a data frame with 5 columns and I want ...
- 111
0
votes
0
answers
19
views
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
0
answers
21
views
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
votes
0
answers
45
views
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
votes
0
answers
10
views
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
0
votes
0
answers
20
views
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
votes
0
answers
11
views
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
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 ...
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: ...
- 3,990