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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I have a 3 class classification problem. Detection of one of classes is very important. How to design the problem? one class classification or ...?

I have a 3 class classification problem. Correct detection of one of the classes is very important. How to design the problem: one class classification? a normal 3 class classification? two distinct ...
27 views

Is the case of a big state space, should we use a softmax exploration policy rather than $\epsilon$-greedy for Q-Learning?

In Reinforcement Learning, epsilon-greedy policies are the most used exploration policies, but in case there is a big state space (let's consider 100,000 states and 2,000 actions) with impossible ...
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AI for text extraction and text recognition

Starting from text I'd like to be able to identify specific informations. Example : Input texts : "The invoice number is 18", "Inv : 75", "Inv N. : 84" Identified invoice ...
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How should $\epsilon$ decay be done?

I am new to reinforcement learning and I am trying to understand the relationship between its hyperparameters. When I use tabular methods, like Q-learning and SARSA, I know that for SARSA the agent ...
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Identifying country name with input as country national anthem audio sound wave file [closed]

Identifying country name with input given as country national anthem audio sound wave file. Identify the country name. This could be a good quiz question in General Knowledge (GK). What are the ...
12 views

Implement 4D convolution as matrix-matrix multiplication - paper is confusing!

I am confused by this paper https://arxiv.org/pdf/1410.0759.pdf which displays on page 4 how to model a 3D convolution (input has more than 1 channel and filter has more than one output). In this ...
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Is it possible learning convergence is lost in Reinforcement Learning as the state space grows? What about catastrophic forgetting?

I am new in the AI field and I am trying to use Reinforcement Learning, Q-Learning and Sarsa algorithms to solve a sequential decision making problem. When I apply those algorithms to a problem with 6....
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25 views

How to update item and user factors ALS in Group Specific Recommendation?

I have also asked this question on our Data Science site. I was going through this Group Specific Recommendation System paper. I want to implement this from scratch. I see that they have used ...
30 views

If I can repeat ML experiments, how can I bound my results?

It has been asked here if we should repeat lengthy experiments. Let's say I can repeat them, how should I present them? For instance, if I am measuring the accuracy of a model on test data during some ...
25 views

Identifying country name with input as country flag image [closed]

Identifying country name with input given as country flag image. Identify the country name. This could be a good quiz question in General Knowledge (GK). What are the machine learning algorithms to ...
181 views

How does learning the moves of chess show up in a neural network?

Is learning the moves a special case or just the same sort of thing that happens as the AI learns strategy? If you take two different neural networks and teach them each how the pieces move, what ...
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Target attribute with comma separated side effects. For th the classification problems [closed]

data set consists of independent variables as age, sex,effectiveness,satisfaction which represents the age, gender and five star satisfaction and effectiveness ratings related to 300k plus drugs. All ...
1 vote
46 views

What is the difference between features and inputs in machine learning?

I have seen many places that features and inputs have been used interchangeably when talking about machine learning especially deep neural networks. I want to know if they are indeed the same thing or ...
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What do "large variables" and "small weights" mean in these sentences?

I'm trying to understand these two points from an article: Models with large variables i.e weight matrices. As a consequence such models have correspondingly large gradients and optimizer states. The ...
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Build the architecture of an ensemble model for tabular classification

I have data that looks like this: ...
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How to inform the autograd, my network structure includes RNN or LSTM? [closed]

Among all the Neural Network structures that are introduced, RNN has received noticeable attention because of the state art included in its gradient computation with backpropagation. On the other hand,...
15 views

How to use oxford5k for training?

Generally, we have training data with landmark IDs, their GTs (positive samples), and then separate query images and corresponding positive samples for evaluation. In the Oxford5k or ROxford5k, one ...
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Can you train GPT-J to use a specific list of words and prioritise them?

Can you train GPT-J to use a specific list of words and prioritise them? If so, please could you share how I would go about this? Say you're using GPT-J to write a story, you might wish to mention ...
1 vote
38 views

Why does the SVM perform poorly on test data that has a different class distribution than the training data?

Do you know why the SVM performs poorly on test data that has a different class distribution than the training data? The training data has around 15 classes, and the additional testing data has around ...
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What is a 'degenerate run' in evaluating model performance?

I've recently come across a paper that uses the term "degenerate run", but I'm not sure if I understand what it means. The idea is that when they report the average performance of running ...
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1 vote
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What happens if all the features are correlated with each other before clustering?

I know that when two features are highly correlated with each other, one of them should be removed from the dataset so they don't add twice the weight. However, what if all my features share a ...
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How to understand the GCN equation?

I understand GCN does message passing with its neighbours to learn the node embedding. But I don't understand the following equation. What "tilda" is referring to equation ...
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When I give an input to a NN, it is generally assumed that the inputs are independent?

I am trying to find a pattern in various measures of health of an individual and using NN. I am using various parameters: Blood Work Some measure of heart condition - turning ECG reading into a ...
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What is your training time of Resnet-18/Resnet-50 on Imagenet?

My training of Resnet-18 network on Imagenet using Tesla V100 seems to be quite slow (1 epoch is about 2,5 hours, batch 128). Increasing the number of GPUs does not seem to help. What is your training ...
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Is there any research on anger and distrust detection (presence and level of political cynicism)?

The undergrad research project I'm working on would require me to detect presence and level of political cynicism from reddit posts. According to definition political cynicism consists of anger ...
74 views

How to deal with an unbalanced dataset?

I'm constructing a feed forward neural network that predicts whether a patient will get a stroke or not. However, my dataset is very unbalanced. Out of 5111 rows, 250 contain patients that have had a ...
22 views

At which step in faster R-CNN is non-maximum suppression performed?

At which step in faster R-CNN is non-maximum suppression performed? In some book, I have read that it is performed after passing the features through the last fully connected layers, which are located ...
54 views

Is there way to segment an image without labeling/classification, as well as supervised learning?

Is there way to segment an image without labeling/classification, as well as supervised learning? For an illustrative example, if one considers an image with a dog and a cup (we don't particularly ...
16 views

Why does loss function and constraint touches at corner point in lasso regression?

As you can see in the picture, for two co-efficient w1 and w2, our loss function, f(w1, w2) should be minimized under constraint function g(w1, w2). For lasso regularization minimum point always lies ...
42 views

How to represent multi-label colours in one-hot encoding?

Say I want to predict the price of a gemstone based on its colour. I have two options: averaging over its colour on an RGB scale, or using its textual description. If I was to choose the latter, how ...
42 views

Which algorithm can find the best combination of players to maximize the chance of getting a high score?

I am looking for the right terminology for this problem, so I know what to learn about. Imagine a population of 100 people in a town. The town has a sport team with 10 positions that play in ...
59 views

Does the term "data augmentation" imply increasing the training dataset?

I have a manuscript which has been reviewed and one of the reviewer commented on my use of the term "data augmentation", saying that it might not be the appropriate term in my case (...
18 views

What are the differences between BLEU and METEOR?

I am trying to understand the concept of evaluating the machine translation evaluation scores. I understand how what BLEU score is trying to achieve. It looks into different n-grams like BLEU-1,BLEU-2,...
18 views

How do I perform automatic evaluation of my NLP model?

I have a model which converts sets of keywords to sentence, but I've to quantify it's quality. In computer vision, we would calculate the model's accuracy, I'm kind of lost and how do I go about using ...
1 vote
55 views

What are the steps to derive the original GAN loss function from the generalized version?

I am trying to understand how the loss function from the original GAN paper \min_{G} \max_{D} V(D, G)=\mathbb{E}_{\boldsymbol{x} \sim p_{\text {data }}(\boldsymbol{x})}[\log D(\boldsymbol{x})]+\...
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Which rule could I use to identify suppliers who are likely to leave us or stay with us?

I have 3 domains of supplier data (Jan 2017 to Jan 2022) and they are as follows Purchase data - Contains all the purchase (of product) data made by the suppliers with us. It contains columns such ...
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Object Classification: How to decide which detected region is a RoI for classification?

I am working on a project where I am working on the Flickr-47 dataset to do logo detection and classification. My approach is to first finetune a YOLO v5 model with high recall to detect as many "...
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1 vote
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Backprop to calculate mean and standard deviation in batch normalization?

On page 310 of the Deep Learning book by Ian Goodfellow (Page 310 can be viewed here for better context: https://www.deeplearningbook.org/contents/optimization.html ), it is mentioned that one crucial ...
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Is attention always better then an RNN/CNN?

We've all read the attention is all you need paper, but is it really all you need? Can you effectively replace any RNN/CNN with an attention transformer and see better results?
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How do I use A.I. to analyse & score news articles?

I'm working on a project that would benefit from using A.I. or machine learning to analyse news feeds from a variety of websites and grade each article between 0 and 10. We would manually grade ...
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1 vote
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How does SGD training error decrease in subsequent epochs when statistically, it requires that samples in subsequent epochs be i.i.d and they are not?

I have been reading the Deep Learning book by Ian Goodfellow and on pg. 277, they mention: It is also crucial that the minibatches be selected randomly. Computing an unbiased estimate of the expected ...
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Why are Siamese Neural Networks used instead of a single neural network?

Siamese Neural Networks are a type of neural network used to compare two instances and infer if they belong to the same object. They are composed by two parallel identical neural networks, whose ...
19 views

Where Can I Find Resources on Extracting Meaningful Content From Web Pages?

I am in the process of conducting a literature review for my thesis. Currently, I am struggling when it comes to developing a theoretical framework/methodology or to even correctly outline an approach ...
58 views

Is it possible to train an AI to bring a picture story in the correct order (correct story flow)?

I want to know if it is possible to train a neural network (or some other kind of an AI) to bring a simple picture story in the correct order, if it is in random order, so that the story has the ...
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Extracting information from bills, tax statements, etc: What ML model to use?

I have a bunch of documents such as bank statements, utilities bills, personal expenditure invoices, etc. The document types range is very broad. Some of these files are saved as pictures, others as ...
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What are the benefits of using spectral k-means over simple k-means?

I have understood why k-means can get stuck in local minima. Now, I am curious to know how the spectral k-means helps to avoid this local minima problem. According to this paper A tutorial on Spectral,...
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Appropriate machine learning approach for object detection of connector

I am suppose to detect a female connector which happens to be an automotive part. I need to draw a bounding box around the connector when it appear. Here's the closest resemblance part I could find to ...
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Which ML algorithm/model should I use to learn temporal dependencies between binary variables?

Let's consider the following setting: We have 1000 binary variables (X1 ... X1000). At each time step each of the variable can either switch (1 to 0 or 0 to 1) or stay the same. I am looking for a ...
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Does this modified version of the triplet loss function introduced with SBERT that uses the cosine similarity make sense?

I am working on a modified version of the triplet loss function introduced with SBERT, where instead of the Euclidean distance we use the cosine similarity. The formula to minimize is ...
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