Questions tagged [features]

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

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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 ...
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1answer
22 views

Does feature scaling have any benefits if all features are on the same scale?

By scaling features, we can prevent one feature from dominating the decisions of a model. For example, say heights (cm), and age (years) are two features in my data. Since range of heights is larger ...
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1answer
43 views

Does the weight vector form imply feature space curvature?

I came across this sentence when exploring a simple nearest neighbor classifier method using Euclidean distance (link): The slightly odd thing about using the Euclidean distance to compare features ...
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1answer
64 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 ...
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1answer
27 views

Is it possible to flip the features and labels after training a model?

The goal of this program is to predict a game outcome given a game-reference-id, which is a serial number like so: id,totalGreen,totalBlue,totalRed,totalYellow,...
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0answers
39 views

In AlphaZero, which features are one-hot encoded and which are single real-valued?

From the AlphaZero paper, the caption of Table S1 (p. 13) Table S1: Input features used by AlphaZero in Go, Chess and Shogi respectively. The first set of features are repeated for each position in a ...
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2answers
114 views

What does the depth of a decision tree depend on?

In these notes, we have the following statement The depth of a learned decision tree can be larger than the number of training examples used to create the tree This statement is false, according to ...
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1answer
39 views

What is the impact of the number of features on the prediction power of a neural network?

What is the impact of the number of features on the prediction power of an ANN model (in general)? Does an increase in the number of features mean a more powerful prediction model (for approximation ...
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0answers
42 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 ...
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1answer
29 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 ...
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2answers
28 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, ...
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1answer
215 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?
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77 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 ...
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1answer
45 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 ...
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0answers
57 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 ...
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1answer
361 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 ...
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1answer
35 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., ...
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1answer
42 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 ...
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0answers
55 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 ...
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0answers
40 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 ...
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0answers
96 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,...
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1answer
42 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 ...
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2answers
90 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 ...
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1answer
1k 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?
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2answers
70 views

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 ...
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2answers
121 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 ...
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1answer
224 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 ...
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1answer
253 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 ...