Questions tagged [machine-learning]
Questions about computer algorithms that automatically discover patterns in data and make good decisions based on them.
1,102
questions
0
votes
0answers
11 views
Discrete action space for MADDPG
I am trying to apply MADDPG to a project. In the work from Lowe et al, the actor returns a pmf for a discrete actions pace. If I set it to Discrete(5) for each agent, it would return something like [0....
1
vote
1answer
9 views
Pruning: Outlier Candidate Selection
I am using method 3.3 described in Outlier Detection using Isolation Forest and Local Outlier
Factor .
It states:
Specify a dataset: $๐ท={๐_1, ๐_2, ..., ๐_๐}$.
Here, ๐ is the sample number of ๐ท. ...
0
votes
0answers
12 views
How to Plot Logistic Regression using Seaborn? [closed]
I am trying to plot logistic regression model but seaborn regplot does not worked. What should I do?
-1
votes
0answers
73 views
explain CompuBERT
My question is about the paper Three is Better than One Ensembling Math Information Retrieval Systems (a system used for math information retrieval - both for finding answers and formula search)(code ...
2
votes
1answer
29 views
Raising to the T in machine learning
What does it mean when in a machine learning paper there is
$(arg)^{T}$, what does the T does to an arg in this 3b1b video on neural networks he puts the: $(w^{l-1})^{T}$
1
vote
0answers
80 views
Which features can be considered for neural network based SAT solving?
I'm trying to implement SAT solver, based on backtracking algorithm and BCP. This SAT solver is trying to pick one literal from each clause, from 3-CNF SAT instances. I've implemented a neural network ...
1
vote
1answer
36 views
PAC learning: success of learning when receiving a sample from a different distribution
I've come across this question and I think I'm on the right track with the idea I just don't really know how to formalize it properly or understand why everything said in the question is required for ...
2
votes
1answer
14 views
Structuring a Regression Model for NCAA Basketball Spreads/Totals
I have a basic linear regression model that predicts the spread and total points of NCAA college basketball games. My inputs include various efficiency metrics about each team playing each other. A ...
0
votes
0answers
35 views
Choosing unsupervised learning algorithm for analyzing the spectrum of a linear operator
I am a theoretical physicist, and new to CS.stackexchange, and have a little knowledge of CS, and in Machine Learning (only some general stuff). In physics we often analyze the spectrum of linear ...
1
vote
2answers
33 views
What computational complexity classification does autonomous/self-driving cars belong to?
Self-driving car technology continues to attract popular attention and interest in today's media, but how would a computer scientist explain the theoretical nature of the problem? For example, we are ...
3
votes
2answers
148 views
Proving a certain hypothesis class on a given distribution is not learnable
I had this question in Learning theory, but it's really just a question in probability theory to be honest, so I'm gonna try to rephrase it in a way that really emphasizes what I was trying to do to ...
0
votes
0answers
25 views
Coordinate descent for Lasso, Question about algorithm
I'm not sure why the algorithm computes $c_k$ with $\sum_{j \neq k} w_j x_{i, j}$. Why does one need to ignore the $k^{th}$ feature here? I'm not sure how this is derived. Is this the result of taking ...
1
vote
0answers
14 views
Where can I learn theoretical aspect of Reinforcement learning
Every RL paper has a section with some finite sample analysis/error bound/ convergence proofs. I have difficulty fully understanding such proofs and coming up with my own analysis for my personal ...
-2
votes
0answers
17 views
What is the Cross Entropy Loss for this output?
Suppose you flip a coin 5 times each with equal probability (let us say 50%, for all 5 coin flips), Would the cross entropy of the function be 1 due to them having no difference in values?
Edit: In a ...
3
votes
1answer
66 views
AdaBoost - why using such alpha function?
I'm reading the paper where AdaBoost was invented (link), and I couldn't understand why they have chosen the formula ฮฑ_t = 1/2 * ln((1-ฮต_t) / ฮต_t).
snippet:
...
1
vote
1answer
54 views
Could AI be used to detect when a human is picking survey response options randomly?
Context: I am a clinical psych researcher dabbling in machine learning.
Humans cannot be truly random. Therefore, could machine learning be used to analyze a string of numbers and determine the ...
0
votes
1answer
31 views
Linear Discriminant Method as Pre-processing for inputs going into a Neural Network?
As the title suggests, I am curious whether Linear Discriminant Method can be performed on a dataset as pre-processing before putting the reduced-dimensional data as input for a neural network for ...
0
votes
1answer
36 views
PCA applicability
I understand that PCA takes a data set with input size, with output labels, and reduces the inputs to a set of principal components size r, where r < n.
My question is whether or not this can be ...
1
vote
1answer
15 views
How to give the nearest text that the user has written
In my database I have 1500 food dishes, not all are single words, there are compound words like "cheese with dried fruit and nuts". And I have them in 5 languages (de, en, fr, es, it).
My ...
1
vote
1answer
20 views
What is the purpose of manipulating trained layers?
In my course there are a number of exercises which amount to taking a trained residual network and deleting, swapping or repeating layers (without retraining).
Is there any real application for doing ...
0
votes
0answers
14 views
When outputting every timestep of an LSTM, is outputs in timesteps with missing training data also affected by overfitting?
I'm referring to things like the "timedistributed" layer in Keras or how in Pytorch LSTM the output is included in every timestep.
An example illustrating my question, say I'm trying to ...
1
vote
0answers
27 views
Proving facts in inverse reinforcement learning [closed]
I was going through paper titled "Algorithms for Inverse Reinforcement Learning" by Andrew Ng and Russell.
It states following basics:
MDP $M$ is a tuple $(S,A,\{P_{sa}\},\gamma,R)$, where
...
0
votes
0answers
10 views
How to use XML format of graphs in Graph neural network?
I have manually labeled directed graphs that I need a GNN to train on and then predict when given a new directed graph, what the labels for the vertexes in the graph should be. My graphs are in the ...
0
votes
1answer
13 views
What is beta and k parameter in Incremental Decision Tree
I have read this paper https://arxiv.org/pdf/1803.03674v1.pdf for outlier detection problem with real data (online training)
In this paper, the authors used Incremental Decision Tree to build ...
29
votes
4answers
9k views
Why can't we mimic a dog's ability to smell COVID?
As far as I can tell, we have invented tools and algorithm to:
Detect a wider range of colors at a larger range than humans or any other animals on the planet
Detect sound with wavelengths ...
2
votes
1answer
21 views
Basic exercises on decision trees
I am a pure math person doing some ML self-study and I am pretty lost.
I am trying to solve the following exercises on decision trees:
Exercise 1. Consider the following training set where
$X_1,X_2,...
1
vote
0answers
25 views
Why do we use different cost functions in machine learning?
In most machine learning applications, we use Maximum Likelihood Estimation to derive appropriate cost functions. For example, if we assume that our model $f(x;\theta)$ yields the mean of a ...
0
votes
0answers
30 views
CNN and relearning
I was suggested to post my question here...
An original my question is
https://stackoverflow.com/questions/66421719/cnn-and-relearning
I would like to train my network with CNN. My image data set is ...
0
votes
0answers
21 views
Does Linear Discriminant Analysis make dimensionality reduction before classification?
I'm trying to understand what LDA exactly does when used as a classifier, i've understood how the dimensionality reduction works and i've understood that the classification task is carried out with ...
5
votes
1answer
160 views
What algorithm do SVMs use to minimize their objective function?
Support Vector Machines turn machine learning linear classification tasks into a linear optimization problems.
$$ \text{minimize } J(\theta,\theta_0) = \frac1n \sum_1^n \text{HingeLoss}(\theta,\...
0
votes
0answers
27 views
why divide norm of w in svm
So I get this through the math behind the SVM (Support Vector Machine), and I get this formula
$$(w^T)(x_1-x_2) = 2.$$
We then divide both side with norm of $w$ then we get the new formula
$$ \frac{w^...
0
votes
0answers
8 views
Which model to apply on such panel data with so may rows but for each unique id rows are 6-8 rows per unique id?
I am new to such panel data where I have multiple observation for same ID in different Quarter and I am not sure what kind of machine learning algorithm I can apply.
I have data from Q1-18 till Q4-...
0
votes
0answers
7 views
How is the dimensionality of the volume in ConvNets determined for a general case?
In ConvNets, I understand how the dimensionality of a flat image changes after convolving it with a single filter. For example, if you convolve a P x P x 1 image (assume no padding) with a filter with ...
0
votes
0answers
24 views
Looking for references for real-world scenarios of data-poisoning attack on labels while doing supervised learning
Consider the following mathematical model of training a neural net : Suppose $f_{w} : \mathbb{R}^n \rightarrow \mathbb{R}$ is a neural net whose weights are $w$. Suppose during the training the ...
0
votes
1answer
24 views
Is any of the assumptions hold true for the mentioned?
Suppose the use of linear regression. The result of the MSE is 120.5(mean squared error) for the train-set. Wev'e reached the minimum of training the data.
Is it possible that by applying Lasso(L1 ...
1
vote
0answers
12 views
What is spatial information in neural network? [duplicate]
The architecture of the CNN model contains several convolutional layers, non-linear activations, batch normalization, and pooling layers. The initial layers learn the low-level concepts such as edges ...
0
votes
1answer
28 views
Is it possible to do face recognition with just the eyes?
Assuming the input photo is focused on a person's face, if the person is wearing a surgical mask, most face recognition software fail to identify the subject's face.
Most facial landmark models are ...
-1
votes
1answer
49 views
Kohonen, 1 dimension, SOM, puzzle
We consider training one-dimensional open map of Kohonen with neurons in one-dimensional input space. We assume it is completed the phase of the device and the weights $w_i$, $i = 1,2, \dots, N$, are ...
1
vote
0answers
22 views
Even distribution of weighted sums across a period of time
I want to automatically&optimally split and distribute a number in several buckets as evenly as possible across a period of time.
Example:
5000 across 12 months, in 6 buckets, with weights 15%, ...
1
vote
1answer
52 views
How does Gradient Descent treat multiple features?
As far as I know, when you reach the step, in a gradient descent algorithm, to calculate step_size, you calculate ...
1
vote
0answers
36 views
Reinforcement learning and Graph Neural Networks: Issue with entropy [closed]
I am currently working on an experiment to link reinforcement learning with graph neural networks.
This is my architecture:
Feature Extraction with GCN:
there is a fully meshed topology with ...
0
votes
1answer
13 views
What exactly is label noise?
I've been doing research on precollege summer programs, and one ongoing project that has come up is "Improving Label Noise Robustness with data Augmentation and Semi Supervised Learning". So,...
1
vote
1answer
23 views
Is transfer learning applied on only similar datasets only?
I am trying to make a CNN model on different brands of logos . Firstly , I wrote a CNN from scratch and trained it on which I got 70% accuracy, I have total 40 classes and each class has 100 images . ...
1
vote
0answers
46 views
Best algorithm/model to establish relevance between events utilizing mixed data type (Tags, Time, x_coordinate, y_coordinate)? [closed]
I'm building a relevance ranking system for incidents occurrence and prevention. My goal is to use four attributes to establish relevance: tag (About 500 tags), x_coordinate, y_coordinate and time. ...
0
votes
0answers
17 views
Are Learning Classifier Systems considered (learning) agents?
Does a LCS model a learning, rule-based agent or does a LCS just implement the agent program (mapping of inputs to actions)?
According to Russel & Norvig :
agent = architecture + agent program
...
1
vote
1answer
50 views
What is the Number of epochs with no improvement after which training will be stopped.?
I am trying to make a Convolutional neural network. Training the images of different brands of Logos. Have 100 images per class and there are 40 classes. I have trained the model now want to check ...
0
votes
1answer
37 views
How does CNN deal with rotation invariant pictures?
I am trying to make a CNN model . Training the image . Want to know that When we apply kernel on image and take out the features of images. That features are rotation invariant or we have to apply ...
0
votes
0answers
14 views
How do I choose the right model for production?
I am trying to build a classification algorithm having 28 classes. These classes consists of Logo of companies like adidas , Nike etc. I have very low dataset below than 100 images and greater than 70 ...
1
vote
1answer
32 views
Which pretrained model will be best for my dataset?
I am trying to build a classification algorithm having 28 classes. These classes consists of Logo of companies like adidas , Nike etc. I have very low dataset below than 100 images and greater than 70 ...
0
votes
0answers
30 views
Human brain controlled computer
It is already possible to let a computer drive the human brain to some limit like for example in the medical world, but will it be possible to let the human brain control a computer system by directly ...
