All Questions
73 questions
2
votes
1
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439
views
Is it true that channels always represent colours of an image?
Convolutional neural networks are widely used in image-related tasks in artificial intelligence.
The input of a conventional neural network is generally an image. The output of a convolutional neural ...
- 33.3k
0
votes
1
answer
90
views
Why disentangling the features of variation in representation?
Consider the following excerpt from abstract of the research paper titled Better Mixing via Deep Representations by Yoshua Bengio et al.
It has been hypothesized, ...
CommunityBot
- 1
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 ...
- 41.4k
3
votes
2
answers
122
views
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 ...
- 41.4k
1
vote
1
answer
53
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 ...
- 868
2
votes
1
answer
69
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 ...
- 1,040
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 ...
- 41.4k
1
vote
2
answers
3k
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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 ...
CommunityBot
- 1
0
votes
1
answer
77
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,...
- 41.4k
0
votes
1
answer
687
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 ...
- 2,660
2
votes
2
answers
466
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 ...
- 41.4k
4
votes
1
answer
7k
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?
- 41.4k
2
votes
2
answers
152
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 ...
- 880
3
votes
1
answer
77
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 ...
- 1,755
5
votes
0
answers
69
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 ...
- 101
5
votes
1
answer
2k
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 ...
- 41.4k
3
votes
1
answer
83
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.,
...
- 121
2
votes
1
answer
562
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 ...
- 41.4k
0
votes
1
answer
90
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 ...
- 375
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
6
votes
1
answer
505
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 ...
- 41.4k
2
votes
2
answers
687
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 ...
- 41.4k
1
vote
1
answer
5k
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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