Questions tagged [feature]

For questions related to features in the context of machine learning and, in general, AI.

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6
votes
1answer
249 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 ...
5
votes
1answer
267 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 ...
4
votes
0answers
50 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 ...
3
votes
1answer
37 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 ...
3
votes
1answer
34 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., ...
2
votes
1answer
198 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 ...
2
votes
2answers
70 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 ...
2
votes
1answer
22 views

Does bag-of-words method improve the classification accuracy?

I'm a beginner in computer vision. I want to know which structure among the following two can get better accuracy of image classification. Structure 1: SIFT feature + SVM Structure 2: bag-of-word ...
2
votes
0answers
41 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 ...
2
votes
0answers
28 views

Does coarse coding with radial basis function generate fewer features?

I am learning about discretization of 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 this ...
2
votes
2answers
59 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 ...
2
votes
2answers
97 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 ...
1
vote
1answer
57 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?
1
vote
1answer
813 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?
1
vote
1answer
17 views

When adding a feature is useless?

"simple" issue: 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 ...
1
vote
0answers
64 views

Multiple embedding layers?

How would one go about inputting multiple high dimensionality categorical columns using TensorFlow's Embedding Feature Columns? Does that even make sense to do? For example: for a car price predictor,...
1
vote
1answer
40 views

Convolution layer neurons when extracting multiple feature maps

I've recently been reading up on CNNs and this part of the architecture is really confusing me. Assume, I have an input of size [32*32*3] and pass it to a convolution layer. Now, if my kernel size ...
0
votes
0answers
20 views

Why is it that having a duplicate in features set makes training to work bad

I'm defining a deep network to emulate a multitarget regression. When I costruct my training set, I take information from a graph; without going into too much detail, it could happen that I take 2 ...
0
votes
2answers
16 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, ...
0
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0answers
23 views

What are the frameworks for automated feature engineering?

I want to ask you what are the frameworks or scientific papers that deal with automated feature extraction/engineering (not based on domain knowledge)? What I mean by feature extraction or ...
0
votes
1answer
32 views

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 ...