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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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 ...
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43 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.
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45 views

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 ...
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47 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 ...
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58 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 ...
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1answer
79 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 ...
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1answer
90 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 ...
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49 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 ...
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27 views

accessible subset of data impacts performance

I have a problem with a subset of my data which is as follows: I can train a model (doesn't matter what, xgboost, BERT, etc., it is a text classification problem), on my data and get a decent ...
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25 views

Binary classification to recognize blobs on pictures generates many false-positive results

I am training a NN for blobs vs non-blobs recognition. Blobs example: Non-blobs: Keras architecture is: ...
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1answer
35 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 ...
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2answers
53 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)?...
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1answer
42 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 ...
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27 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 ...
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21 views

Input with variable length Classification problem

I have a dataset with patient information with discrete labels (labels are stages of a particular disease) which needs to be predicted (Basically a classification problem). The data set looks ...
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50 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 ...
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1answer
68 views

Bayes error rate formula clarification

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 - \...
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29 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 ...
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28 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 ...
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29 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 ...
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26 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 (...
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18 views

How can I efficiently detect subsections?

I have a feeling this question has a lot of research into it, but I can't find any relevant results. I'm trying to compare the similarity of audio Here, I have 2 virtually identical samples; however,...
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26 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 ...
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28 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 ...
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2answers
74 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 ...
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1answer
40 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 ...
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13 views

Would truncating a trained CNN help with generalisation?

Say I have a very small dataset to do transfer learning with, for image classification purposes. And say that I know that what's most important in classifying these images is low level details like ...
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1answer
33 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 negative ...
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1answer
46 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 ...
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0answers
23 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 ...
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28 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 $t$. ...
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3answers
110 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 ...
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1answer
55 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 ...
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0answers
29 views

Single label classification into hierarchical categories using a neural network

I am working on a classification problem into progressive classes. In other words, there is some hierarchy of categories in such a way, that A < B < C, e.g. low, medium, high, very high. What ...
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1answer
25 views

How are weights for weighted x-entropy loss on imbalanced data calculated?

I am trying to build a classifier which should be trained with the cross entropy loss. The training data is highly class-imbalanced. To tackle this, I've gone through the advice of the tensorflow docs ...
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5answers
96 views

Which classifier should I use for a dataset with one feature?

I have a labeled dataset composed of 3000 data. Its single feature is the price of the house and its label is the number of bedrooms. Which classifier would be a good choice to classify these data?
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35 views

Are bayesian neural networks suited for text (or document) classification?

I've tried to do my research on Bayesian neural networks online, but I find most of them are used for image classification. This is probably due to the nature of Bayesian neural networks, which may be ...
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0answers
27 views

Why is my SVM not reaching good accuracy when trained to perform binary classification of search results?

I am trying to perform binary classification of search results based on the relevance to the query. I followed this tutorial on how to make an SVM, and I got it to work with a small iris dataset. Now, ...
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0answers
66 views

How to implement a LSTM for multilabel classification problem?

I would like to develop an LSTM because I have a variable input matrix. I am zero-padding to a specific length of 800. However, I am not sure of how to classify a certain situation when each input ...
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1answer
30 views

Running 10 epochs on the Food-101 dataset

I’m currently working on the Food-101 dataset. I want to train a model that is greater than 85% accuracy for top-1 for the test set, using a ResNet50 or smaller network with a reasonable set of ...
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0answers
24 views

How can I implement a Facial Recognition algorithm in C++ from scratch, without using OpenCV?

I wanna implement an algorithm for Facial Recognition in C++ with the help of Viola-Jones, aka Adaboost, but without using OpenCV or any other similar library. I wanna do it all from scratch. Any tips?...
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15 views

How do I decide which norm to use for placing a constraint on my adversarial perturbation?

I am performing an adversarial machine learning attack on a neural network for network traffic classification. For adding adversarial perturbations in features such as packet interarrival times and ...
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1answer
28 views

How to estimate the accuracy upper limit of any CNN model over a computer vision classification task

We are given a computer vision classification task, that is, a task that asks us to predict the category of an image over $n$ predefined classes (the so-called closed set classification problem). ...
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24 views

length independent sequence classification methods

I am looking to do sequence classification using deep learning. The length of my sequences can vary from a few hundred to several tens of thousands of characters. I was wondering what is a good ...
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1answer
30 views

Object detection: combine many classes into one?

I am trying to train a model that detects logos in documents. Since I am not really interested in what kind of logo there is, but simply if there is a logo, does it make sense to combine all logos ...
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0answers
14 views

Data classification model to detect a process in an event log

There are many example in python which has a ready made data set, for example there is T-Shirt pre-trained data and thousands images, within few minutes it will tell how many t-shirt images are there ...
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1answer
510 views

Can neural networks with a sigmoid as the activation function of the output layer approximate continuous functions?

Neural networks are commonly used for classification tasks, in fact from this post it seems like that's where they shine brightest. However, when we want to classify using neural networks, we often ...
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1answer
575 views

How should the neural network deal with unexpected inputs?

I recently wrote an application using a deep learning model designed to classify inputs. There are plenty of examples of this using images of irises, cats, and other objects. If I trained a data ...
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1answer
55 views

How to perform insect classification given two images of the same insect?

I'm relatively new to image classification. Currently, I am trying to classify insect images, using a convolutional neural network (CNN). When I ask a human expert to identify an insect, I usually ...
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2answers
52 views

Using AI to enhance customer service

I'm trying to find out how AI can help with efficient customer service, in fact call routing to the right agent. My usecase is given context of a query from a customer and agents' expertise, how can ...

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