All Questions
Tagged with regressors or features
73 questions
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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 ...
- 23
1
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2
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65
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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,
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4
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1
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7k
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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
2
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152
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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
3
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1
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77
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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
5
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0
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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
5
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1
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2k
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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
3
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1
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83
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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
0
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1
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90
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What is the correct name for state explosion from sensor discretization?
The position of a robot on a map contains of an x/y value, for example $position(x=100.23,y=400.78)$. The internal representation of the variable is a 32bit float which is equal to 4 byte in the RAM ...
user11571
1
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0
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104
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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
1
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1
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71
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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
2
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0
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90
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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
2
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1
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328
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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
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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
1
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1
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510
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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
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1
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5k
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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
2
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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 ...
- 177
1
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2
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250
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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
2
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1
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562
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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
4
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1
answer
76
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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
5
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1
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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 ...
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8
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2
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304
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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
6
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1
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505
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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 ...
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