For questions related to features in the context of machine learning and, in general, AI.
For more info, have a look e.g. at https://en.wikipedia.org/wiki/Feature_(machine_learning).
Questions tagged [features]
57 questions
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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 factor in the value of a single piece of art).
My…
Vince Britz
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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 convolutional networks
Harmonic networks
It…
spiridon_the_sun_rotator
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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 vector as input to an algorithm, which then predicts…
schoon
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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 game like slither.io. So, in order to be able to…
AntonKad
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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 the perspective of the camera, their location…
g491
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5
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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 and the
network performance after conditioning on…
Clumsy cat
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4
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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. Deeper layers tend to recognise more high-level…
mesllo
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4
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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 check layer outputs in a NN, we can see and visualize how…
dasmehdix
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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?
nbro
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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 times, each time for one more day ahead (using…
George
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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 the layers. I've heard this a lot and seen it on videos like…
Daviiid
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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 read the paper, I understand in general terms how…
natanijelvasic
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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.,
EigenVectors: [0.7549043055910286, 0.24177972266822534, -0.6095588015369825, -0.01000612689310429]
EigenVectors: [0.0363767549959317, -0.9435613299702559,…
Crizly
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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 inputs affect the performance (e.g. accuracy) of…
imtiaz ul Hassan
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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 anomalous sample (specifically from MNIST) and a…
Hadar Sharvit
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