Questions tagged [classification]

For questions related to the placement of individual cases into categories, such as is essential in fraud detection, spam detection, quality control, prediction of user or market responses, automated organizing or indexing, assigning objects in view to types of obstacles or risks, writing or typing recognition, phonic recognition, .

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Which ML approach could determine that a number greater than 5 is not prime, knowing that a number is not prime if it ends with an even digit or 5?

I have started studying ML just a short while ago, so that my questions will be very elementary. That being so, if they are not welcome, just tell me and I'll stop asking them. I gave myself a ...
Vni Versvs's user avatar
2 votes
0 answers
26 views

What are ways to learn a classifier for labelling a series of images rather than individual images?

... and how do I reword my question in the title? I have a dataset where each "instance" has a "series" of multiple photos taken from different angles. I need to classify each ...
Alexander Soare's user avatar
1 vote
0 answers
129 views

Where can I find pre-trained agents able to play games with multiple stages like exploration, dialog, combat?

My goal is to create an ML model to be able to classify different game stages, e.g., dialog with a non-player character, exploration, combat with enemy, in-game menu etc. In order to do that, I am ...
bbasaran's user avatar
  • 133
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0 answers
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CNN to detect presence/absense of label on images with mixed labels

Here's my problem: I work with medical image classification, and currently I have 3 classes: class A: images with lesion 1 only; and images with lesion 1 and N other lesions class B: images with 2 ...
lebebop's user avatar
  • 31
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0 answers
19 views

How to classify anomalies between two sound datasets?

I have two sound datasets and each one has 80% normal and 20% anomalous data points. The first one is a rock song and the second one is a mellow indie song. I use half of the normal data as a baseline ...
user14361718's user avatar
1 vote
1 answer
93 views

Single-Shot Learning for Object Re-Identification

I am looking for a way to re-identify/classify/recognize x real life objects (x < 50) with a camera. Each object should be presented to the AI only once for learning and there's always only one of ...
sonovice's user avatar
  • 111
2 votes
1 answer
3k views

Why do we resize images before using them for object detection?

In object detection, we can resize images by keeping the ratio the same as the original image, which is often known as "letterbox" resize. My questions are Why do we need to resize images? ...
CuCaRot's user avatar
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2 votes
1 answer
166 views

Support Vector Machine Convert optimisation problem from argmax to argmin

I'm new to the AI Stackexchange and wasn't certain if this should go here or to Maths instead but thought the context with ML may be useful to understand my problem. I hope posting this question here ...
Joneron's user avatar
  • 21
1 vote
0 answers
48 views

How to find a parameter combination for a black box using AI?

I am working on a project where I encountered a component which takes 96 arguments (all integer values) and outputs 12 float values. I would like to find a useful combination of these 96 values to ...
e.Fro's user avatar
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1 vote
1 answer
214 views

How can I determine whether a video's frame is realistic (was recorded by a camera) or contains computer-generated graphics?

Given a video, I'm trying to classify whether it is a graphical (computer-generated) or realistic scene. For instance, if it contains computer-generated graphics, credit, moving bugs, blue screen, etc....
Tina J's user avatar
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What is the best neural network model to classify an x(t) signal according two classes?

I am a beginner in AI methods. I have a collection of x(t) data, where x are some signal amplitudes and t is a time. My testing data are divided into two classes, say those from good and bad ...
Marek's user avatar
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1 vote
0 answers
117 views

Role of autoencoder in Hierarchical Extreme Learning Machine

I want to build HELM neural network that consists of autoencoder (AE) and one class classification (OC). HELM with AE and OC have following shape: That is, hidden layer output of AE is input of OC. ...
Zekhire's user avatar
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0 votes
1 answer
179 views

How can I train a CNN to detect when a person is smoking outside of shop given images from a video camera?

My friend is working at a pizza shop. He takes cigarette breaks in an area that is covered by the public webcam of our town. I now want to train a convolutional neural network to be able to detect ...
Howard's user avatar
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0 answers
37 views

Loss function for better class separability in multi class classification

So I am trying to enforce better separability in my deep learning model and was wondering what I can use besides cross entropy loss to do that? Could maybe using logarithm with different basis in ...
GreatDuke's user avatar
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3 votes
1 answer
189 views

Comparing a large/general CNN to a smaller more specialized one?

I am still somewhat a novice in the ML world, but I had a strange idea about CNNs and wanted to ask if this would be a valid way to check the robustness of a general CNN that classifies certain images....
User_13's user avatar
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1 vote
0 answers
55 views

Estimating $\sigma_i$ according to maximum likelihood method

Let be a Bayesian multivariate normal distribution classifier with distinct covariance matrices for each class and isotropic, i.e. with equal values over the entire diagonal and zero otherwise, $\...
David's user avatar
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How do you make a regression model from a binary labeled dataset?

Suppose I have a dataset with hand images. Hand completely opened is labeled as 0 and hand completely closed (fist) are labeled as 1. I also have a bunch of unlabeled images of hands which, if ...
offchan's user avatar
  • 325
0 votes
1 answer
244 views

Do we need non-linear activation function in neural networks whose task isn't classification?

While researching why we need non linear activation functions, all the explanations revolve around neural network being able to separate values that aren't linearly separable. So I wonder, if we have ...
user1477107's user avatar
0 votes
1 answer
127 views

Can a neural network be trained on a dataset containing only values for true output for a classification problem?

I am using a dataset from Google which contains 1,27,000 data points on simulated concentrations of the atmosphere of exoplanets which can sustain life. So, the output label of all these data points ...
Niranjan Dindodi's user avatar
0 votes
1 answer
30 views

Which type of feature extractor do you suggest to classify sensor data?

I have IMU (Inertial Measurment Unit- 6 axis) sensor data. The sensor attached on a car and 7 different drivers wipe on same path. I want to extract features and classify drivers. Which type of ...
dasmehdix's user avatar
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1 vote
1 answer
85 views

How can I classify houses given a dataset of houses with descriptions?

I have a dataset with a number of houses, for each house, I have a description. For example "The house is luxuriously renovated" or "The house is nicely renovated". My aim is to ...
Melly Donald's user avatar
1 vote
0 answers
38 views

Is there a problem for "Sound Source Identification in Video Footage"?

I've been considering starting a project for some time on sound source identification. To be more specific, my goal is to be able to identify the "sources" for sound in videos. Moving parts ...
madprogramer's user avatar
0 votes
2 answers
86 views

How do I classify whether a document is legal or not given a set of keywords that appear only in legal documents?

Let's say that I want to classify whether a document is a legal document or not. I have a list of keywords that will be presented only in legal documents. What is the proper way or algorithm to ...
ahmadMarafa's user avatar
1 vote
0 answers
47 views

Does Algorithmic Mechanism Design come under the field of AI?

I see many papers in AAMAS talk about artificial intelligence and mechanism design simultaneously. I was wondering, for the sake of being pedantic, is mechanism design could be classified under AI.
kosmos's user avatar
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Extending patch based image classification into image classification

I am trying to classify tampered, pristine images from set of images, in that I have built a network in which I would divide the image into multiple overlapping patches and then classify them into ...
kiran's user avatar
  • 21
1 vote
0 answers
51 views

Which neural network should I use to distinguish between different types of defects?

I want to teach a neural network to distinguish between different types of defects. For that, I generated images of fake-defects. The images of the fake-defect types are attached. I tried many ...
beinando's user avatar
  • 131
0 votes
0 answers
64 views

Finding the 'ultimate resolution' of an ANN

I want to use a neural network to predict the refractive index of a solution. My thinking is, instead of immediately training on many samples, I will first find the 'ultimate resolution' of the ...
ngc1300's user avatar
  • 133
5 votes
1 answer
2k views

Which paper introduced the term "softmax"?

Nowadays, the softmax function is widely used in deep learning and, specifically, classification with neural networks. However, the origins of this term and function are almost never mentioned ...
nbro's user avatar
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3 votes
1 answer
200 views

Is it possible to classify resistors using ResNet50?

I want to train ResNet50 model using resistor images like below: I tried it by collecting data from google images and there were quite few. So accuracy was very low (around %10) but I wonder If it is ...
Nabla's user avatar
  • 192
2 votes
0 answers
77 views

Why is 'scatter' used instead of variance in LDA?

I've been reading about Fisher's Linear Discriminant Analysis lately, and I noticed that the objective function (particularly for two-class classification) to be maximized contains scatter terms ...
stoic-santiago's user avatar
0 votes
1 answer
56 views

What is the advantage of having a stochastic classification procedure?

What is the advantage of having a stochastic/probabilistic classification procedure? The classifiers I have encountered so far are as follows. Suppose we have two outcomes $A = \{0,1\}$. Given a ...
MMM's user avatar
  • 185
1 vote
2 answers
267 views

Why don't we use trigonometric functions for the output neurons?

Why don't we use a trigonometric function, such as $\tan(x)$, where $x$ is an element of the interval $[0,pi/2)$, instead of the sigmoid function for the output neurons (in the case of classification)?...
AC18's user avatar
  • 13
1 vote
1 answer
331 views

How to use speaker's information as well as text for fine-tuning BERT?

I want to classify my corporate chat messages into a few categories such as question, answer, and report. I used a fine-tuned BERT model, and the result wasn't bad. Now, I started thinking about ways ...
k4200's user avatar
  • 111
1 vote
1 answer
67 views

How to split data into training validation and test set when the number of data in classes varies greatly?

I have 5 classes of pictures to classify: 0 -> ~3 200 (~800 initial number before interference and duplication) 1 -> ~9 000 (I reduced from ~90 000) 2 -> ~8 000 3 -> ~3 000 4 -> ~7 200 How to ...
Dominiksr's user avatar
1 vote
0 answers
61 views

Is subsection generation $O(n^4)$

When I say template matching, I'm referring to finding occurrences of a small image (the template) in a larger image. The OpenCV library provides the trivial solution, that slides the template over ...
Tobi Akinyemi's user avatar
4 votes
1 answer
534 views

How is the formula for the Bayes error rate with an integral derived?

My questions concern a particular formulation of the Bayes error rate from Wikipedia, summarized below. For a multiclass classifier, the Bayes error rate may be calculated as follows: $$p = 1 - \sum_{...
EntangledLoops's user avatar
1 vote
0 answers
111 views

How can I predict the label given a partial feature vector?

Most of the traditional machine learning algorithms need a feature vector of a constant dimension to predict the label. Which algorithms can be used to predict a class label with a shorter or ...
Atena's user avatar
  • 131
2 votes
0 answers
47 views

Incorporating domain knowledge into recurrent network

I am currently trying to solve a classification task with a recurrent artificial neural network (RNN). Situation There are up to 350 inputs (X) mapped on one categorical output (y)(13 differnt ...
DoKi's user avatar
  • 31
2 votes
0 answers
36 views

Is there a classification task with multiple attribute regression?

I'm trying to look for a task that predicts a discrete label first (classification), and then predicts the multiple continuous attributes of the predicted class. I found some papers about multi-output ...
Ahmed Effertz's user avatar
2 votes
0 answers
28 views

How does sampling works in case of imbalanced image datasets?

I am solving a problem of image classification of the image dataset for 3 classes. Dataset is highly imbalanced. How will sampling (either over- or under-sampling) work in that case? Should I remove (...
Beginner's user avatar
  • 121
1 vote
0 answers
63 views

Is the high dimensionality of input vectors a problem for a radial basis function neural network?

I have a dataset A of videos. I've extracted the feature vector of each video (with a convolutional neural network, via transfer learning) creating a dataset B. Now, every vector of the dataset B has ...
AleWolf's user avatar
  • 167
1 vote
0 answers
71 views

Are there any general guidelines for dealing with imbalanced data through upsampling or downsampling?

Are there any general guidelines for dealing with imbalanced data through upsampling/downsampling? This Google developer guide suggests performing downsampling with upweighting, but for the most ...
information_interchange's user avatar
2 votes
2 answers
4k views

Combine two feature vectors for a correct input of a neural network

Let's consider this scenario. I have two conceptually different video datasets, for example a dataset A composed of videos about cats and a dataset B composed of videos about houses. Now, I'm able to ...
AleWolf's user avatar
  • 167
0 votes
1 answer
198 views

Is it a good idea to overfit on a small part of your data for faster model convergence?

I working on a classification problem that needs to detect patterns on a time serie. Basically, there's a catch-all class that means "no pattern detected", the other are for the specific patterns. The ...
Sebastien's user avatar
  • 101
4 votes
2 answers
2k views

What is the meaning of "easy negatives" in the context of machine learning?

What does the term "easy negatives" exactly mean in the context of machine learning for a classification problem or any problem in general? From a quick google search, I think it means just ...
Megh's user avatar
  • 51
2 votes
1 answer
54 views

What are the best classifiers for this type of data?

I would like to classify a dataset Credit Scoring, which is composed of 21 attributes, some of them are numeric and others are boolean. For the output, I want to know if they have a good or bad ...
Ghost X's user avatar
  • 121
4 votes
1 answer
474 views

How should I define the loss function for a multi-object detection problem?

I'm trying to create a text recognition project using CNN. I need help regarding the text detection task. I have the training images and bounding box details for them. But I'm unable to figure out ...
h4x's user avatar
  • 41
1 vote
1 answer
109 views

Does it classify as Machine Learning?

I have a gaussian distributed time series ($X_t$) with some parameters in my experiment. Suppose I want to know the mean $\mu$. If I define another time series $Y_t$ such that $Y_t=X_t-a$ for all $t$. ...
Raunak Dey's user avatar
4 votes
3 answers
4k views

Can I do image classification with Multi Layers Perceptron (MLP)?

I'm seeking guidence here. Can I use Multi Layers Perceptron (MLP), e.g regular flat neural networks, for image classification? Will they perform better than Fisher Faces? Is it difficult to do ...
euraad's user avatar
  • 143
2 votes
1 answer
173 views

An infinite VC dimensional space vs using hierarchical subspaces of finite but growing VC dimensions

I have the following scenario. I have a binary classification problem, whose underlying function is a step function. The probability distribution of feature vectors is a uniform over the domain. Case ...
Rajesh D's user avatar
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