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Questions tagged [machine-learning]

For questions related to machine learning (ML), which is a set of methods that can automatically detect patterns in data, and then use the uncovered patterns to predict future data, or to perform other kinds of decision making under uncertainty (such as planning how to collect more data). ML is usually divided into supervised, unsupervised and reinforcement learning. Deep learning is a subfield of ML that uses deep artificial neural networks.

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What are the formulas for the MAE , MSE when output is a vector?

What are the formulas for the MAE , MSE when output is a vector? MAE: Mean Absolute Error MSE: Mean squared error
DSPinfinity's user avatar
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How to differentiate fuzzy matching from artificial intelligence [duplicate]

I am curious about the term "fuzzy matching," and whether it falls under the category of artificial intelligence. Specifically, when can we say that a website or system is using AI, and when ...
CollarKaniz's user avatar
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70 views

claude 2 doesn't know basic math? [duplicate]

Sometimes, when I see answers like this from large language models, it makes me feel disgusted: Me: Does Voyager 1 have enough velocity to escape the solar system without using Jupiter's gravity ...
Mr Saw's user avatar
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1 answer
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Do WGAN gradients require multi-variable calculus?

The generator tries to maximise this function D(G(z)). That much I understand. But how can the critic maximise D(x) - D(G(z)). ...
zacoons's user avatar
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2 votes
2 answers
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Why any set of m data points with different features can be perfectly fit by a polynomial of degree n as long as n ≥ m

On p.36 in "Machine Learning: The Basics", Alexander Jung, Spinger, the author wrote: The fundamental theorem of algebra tells us that any set of m data points with different features can ...
Tran Khanh's user avatar
2 votes
1 answer
265 views

How to train a sample weight model for another ML model?

I'm trying to train a ML model, however the predictability of the different samples varies, i.e. some samples are inherently much harder to predict/estimate than others. Poorer predictions for these ...
Hiho's user avatar
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1 answer
295 views

How to force Transformer to give more weight to certain tokens

I'm developing an encoder-decoder based transformer model and I would like to ask if there are ways to incentivize or penalize certain tokens during training. I'm working on a translation task where ...
jasperagrante's user avatar
1 vote
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26 views

Is there any well-established work that allows robots to communicate their decision-making using natural language?

I am searching for a well-established work that allows robots to communicate their decision-making using natural language. For example, a robot's explanation could be "I did [task1] because [...
jigz's user avatar
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What is $D_i$ in "Common Principal Components Analysis"?

The following is from Ethem Alpaydin, "Introduction to Machine Learning", Fourth Edition, MIT Press, 2020, page 129. Here, $C$ is the orthogonal matrix found from the sample covariance of ...
DSPinfinity's user avatar
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1 answer
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What is $D_i$ in "Common Principal Components Analysis"?

The following is from Ethem Alpaydin, "Introduction to Machine Learning", Fourth Edition, MIT Press, 2020, page 129. Here, $C$ is the orthogonal matrix found from the sample covariance of ...
DSPinfinity's user avatar
1 vote
1 answer
64 views

Which process is better to understand images?

What is the difference between this process of recognizing objects in a image: (The correlation function calculate the correlation coefficient between the input and a image containing the object we ...
Cerise's user avatar
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autoencoders for anomaly detection, training individual models for different users or roles, how?

Do I first train a generic model for all of my users on a network, say for a network anomaly detection example, then fine tune for each user on their own subset of the training data? But I'd be using ...
mLstudent33's user avatar
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25 views

Convert specific domain knowledge text to a knowledge graph

As part of this semester assignment , I'm working on a project that aims to to represent the knowledge in "PMBOK 6th edition, section 11: Project Risk Management (page 395 -> 458)" and the knowledge ...
Wissem Boujlida's user avatar
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0 answers
11 views

Why is the feature direction chosen in the direction associated with largest eigenvalue of $\Sigma_T$ in case of more than two classes?

Why is the feature direction chosen in the direction associated with largest eigenvalue of $\Sigma_T$ in case of more than two classes? Please see the following.
DSPinfinity's user avatar
1 vote
2 answers
55 views

Data preparation for NLP model

I have data from our ticketing system. Currently using OpenNLP to create different models. For simplicity I have a 10k ticket's text as category final queue of the ticket. My questions: Is it ...
Milkmaid's user avatar
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14 views

Build a global model based on thousand local models

I have 1000 meters for electricity usage. I want to train one global model for all of them to predict their consumption for the next few days. So, when I train the model with all of the meter data, ...
Sadcow's user avatar
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1 answer
466 views

Can Vision Transformers be used to extract features?

Can Vision Transformers be used to extract features, just like with VGG ? I am interested in using this vision transformer in extracting features (https://huggingface.co/google/vit-base-patch16-224) ...
Ahmed Gamal's user avatar
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21 views

In $n$ dimensions, why do we need at least $n+1$ sample points to have covariance of sample data non-singular?

In $n$ dimensions, why do we need at least $n+1$ sample points to have covariance of sample data non-singular?
DSPinfinity's user avatar
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16 views

Requesting resources on causal networks for 2D strategy game

I am requesting research, articles, abstracts or interesting opinions that will help me create a complex causal neural network. There are many detailed resources on causal discovery, image recognition,...
Mitsuformation's user avatar
1 vote
1 answer
129 views

How the generator loss works in a GAN

I've been reading about GANs so I can implement a simple image generator. It seems that the loss for the generator is given by the following equation: ...
zacoons's user avatar
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0 answers
31 views

Confusion about the code for choosing "stumps" in Adaboost algorithm

(I actually asked the following question on Stack Overflow and Cross Validated Exchange for more than a month: https://stackoverflow.com/questions/76842431/confusion-about-the-code-for-choosing-...
Richard's user avatar
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Why does my loss function fluctuate so much?

I have a loss function that I'm trying to maximise using a neural network. While it does appear to increase and plateau over the training, it does so in a very "noisy" manner, spiking up and ...
VJ123's user avatar
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0 answers
25 views

High Accuracy ML.NET Image differentiation model

I have a relatively big dataset (100+GB) that has 35 categories. All of them are microscopic images with slight differences. Although ML.NET documentation itself declares that training time should be ...
Helios Lucifer's user avatar
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0 answers
52 views

Unclear points on feature extraction for a set of scenarios

The following is an example from a book (An Introduction to Pattern Recognition and Machine Learning by P. Fieguth, page 85) on feature extraction and selection. Please consider the following figure. ...
DSPinfinity's user avatar
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1 answer
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What is wrong in reasoning here in classification for defect detection?

Consider the following hypotheses: $H_0$: a given coin is fair $H_1$: a given coin is unfair Let $\alpha$ = P(Classify as $H_1$|Sample actually from $H_0$) We know the statistics for a fair coin, ...
DSPinfinity's user avatar
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8 views

Algorithm Suggestion for Diverging Data (Severity/Intensity Analysis)

I have four datasets for four different accidents; each dataset has the same parameters. Some of the key parameters are changing their values from a "standard value". The more they change ...
Rubayet Alam's user avatar
0 votes
1 answer
143 views

What is the difference between Machine Learning model, algorithm and hypothesis?

I'm fairly new to Machine Learning field and still to grasp the basics, so this question may seem very stupid, but what is the difference between Machine Learning model, algorithm and hypothesis? Like ...
Niharika Patil's user avatar
1 vote
0 answers
106 views

NLP for classifying a YES or NO response to a question

I'm currently working on a project that requires some feature extraction. The data I have is text and comes from an interview. The interviewer asks a question, the client responds, and the interviewer ...
altheconda's user avatar
-2 votes
2 answers
97 views

How successful are the state-of-the-art (2023) email filters really? [closed]

How successful are the state-of-the-art (2023) email filters really? Some references claim that spam detection may reach high accuracy in test settings, but I've thought that email filtering should ...
mavavilj's user avatar
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0 answers
28 views

Query modification for search using AI

I have a problem statement that I'm struggling to formulate as a machine learning framework. There is a huge client database of documents - we're trying to come up with an efficient way of querying ...
user9343456's user avatar
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0 answers
46 views

Are we missing correlation to achieve a artificial intelligence comparable to humans?

I don't think neural networks are enough to copy human intelligence because in the end a machine only using a neural network to decide on something still is unable to recognize patterns. So I was ...
Cerise's user avatar
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0 answers
51 views

Optimizing Stop Loss Percentage for a Specific Model Based on Stock Price to Maximize Expected Value

I'm fine-tuning a specific trading model, and a crucial parameter I'm keen on optimizing is the stop loss percentage. The primary objective is to maximize the Expected Value (EV), formulated as: $$EV =...
David's user avatar
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0 votes
0 answers
23 views

ROC curve for multiclassification - results sound not correct

I'm working on a multiclassification task using LSTM algorithm, i generated my roc curve plots but they give scores like 1 , 0.99, 0.97 however i have an accuracy of 0.97, Precision 0.65, Sensitivity/...
biihu's user avatar
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0 votes
0 answers
37 views

Pixel-wise regression only focus on edge

I am trying to use unet to learn pixel-wise regression from one image to one groundtruth with the same image size. The network seems to focus too much on the edge of the image, and it does not learn ...
K.Nguyen's user avatar
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0 answers
12 views

Challenges in Developing AI Algorithms for X-ray Image Analysis on Large Datasets

Hello everyone, I'm currently working on a research project involving X-ray imaging and the development of AI algorithms to detect diseases from large ...
kibromhft's user avatar
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0 answers
44 views

Understand Memory Usage of Pytorch Tensors for Inference

I plan on translating large text corpora from various languages to english with Large Language Models. Therefore, I tried messing around a bit to see the computational limits of my machine. ...
n_arch's user avatar
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0 votes
0 answers
38 views

MultiLayer Perceptron not working for regression problem, what could I try?

I am trying to learn the inverse kinematics of a robotic manipulator. To do that I have a simulator with which I acquired data. My dataset is composed of positions in X, Y and Z and actuator variables ...
Guillaume's user avatar
4 votes
1 answer
210 views

Training an RL model with an environment where some of the variables do not change as a result of the agent actions

Typically training an RL model requires an action and an observation space, and the agent learns how its actions affect the observations. Even though there are cases where the observation space ...
Jesuspc's user avatar
  • 151
2 votes
1 answer
145 views

Find maximum value of unknown functions f(x,y)=z using reinforcement learning & neural network

is it possible to train a neural network to find the global maximum value of unknown functions like f(x,y)=z with reinforcement learning? Up until now I had only had experience with simple ...
Bubble's user avatar
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0 votes
0 answers
46 views

Using deep reinforcement learning for malware detection; trained agent mostly performs the same action

I'm trying to implement this article: Ransomware early detection using deep reinforcement learning on portable executable header The article uses an unpublished dataset of benign and ransomware ...
soosan123's user avatar
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0 answers
14 views

Implement perceptron given decision boundary function

Suppose we have a linear classifier for the classes ω1 and ω2 with characteristics vectors Xa=[a a]^T and Xb=[-a -a]^T correspondingly. Also suppose that the decision boundary that is defined by ...
TheExtraSpicyBeef's user avatar
2 votes
0 answers
136 views

What's the relationship between Reinforcement Learning (RL) and Markov Chain Monte Carlo (MCMC)?

The title may seem too broad, let me specify this question a bit more. Suppose that there is a problem that can be solved via MCMC-based algorithm, i.e., for its formulation we can construct a Markov ...
Halve Luve's user avatar
0 votes
0 answers
25 views

Loss function increases dramatically after transfer learning (or parameters initialization)

I am modeling a CNN network with some customized layers that performs 2D FFT and IFFT, I have a dataset with features representing time domain OFDM symbols, and labels representing frequency domain ...
Younes Salmi's user avatar
1 vote
1 answer
65 views

How to compute an estimate of the expected value of a stochastic random variable in Reinforcement Learning?

In the section on LSTD in SuttonBarto's book on RL, there is a proof on convergence of semi-gradient TD(0) using a linear function approximator. Later on they estimated A and b as I was under the ...
user75923's user avatar
0 votes
1 answer
22 views

Can we generate labels for an unlabelled dataset by doing some feature engineering?

I am very new to ML and currently, I am working on building a model that can predict recurring blood donors (a classification problem). I have a dataset which consists of 25 features (gender, height, ...
stkmnd's user avatar
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0 votes
0 answers
63 views

How to train a machine learning model using reinforcement learning for Battleship to predict next best move?

Question How can I train a machine learning model to predict best next move using reinforcement learning for Battleship? (using reinforcement learning is the key of this question. I want it to learn ...
jstycrpsc's user avatar
1 vote
1 answer
123 views

How to transform a loss function into a score function?

Loss_Function/Maximize_Function/Score_Function, CustomLoss, pytorch. Using Custom Loss for Maximizing Score in PyTorch I'm using a PyTorch model with an LSTM input layer, a linear hidden layer, and 3 ...
IAQuestions's user avatar
2 votes
2 answers
273 views

How to generate a 3D model from only 1 image?

I'm posting this on the AI stack exchange because even though this can be solved with a "regular" complex and sophisticated algorithm, it seems that trying to generate something for which ...
OGOG's user avatar
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3 votes
1 answer
128 views

How can I improve this toy Graph Neural Network Generative Language model [closed]

Background I'm an undergraduate student with research interests in a field of physics that has significant overlap with graph theory, and a functioning knowledge of how simple neural nets work and how ...
MomentumEigenstate's user avatar
15 votes
6 answers
7k views

Why do many AI bots feel the need to be know-it-alls?

Having used various AI bots often over recent months, I noticed that often it will claim to know something, even if it doesn't. It would then either explain something which is clearly nonsense, or by ...
ben svenssohn's user avatar

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