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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FastAi Image Classification

I am learning DNN from FastAi Part 1.(Deep Learning for coders).While testing the below code ...
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How can I demonstrate my novel machine learning classification model has value in publication?

I designed a machine learning classification algorithm that's simple enough that a comp sci 101 student could code it, relies on very few assumptions, extremely fast and efficient, and surprisingly ...
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How to properly name given type of classification problem?

What is the proper technical name of the classification problem where each data sample can be classified according to two different criteria and each of them can have two or more classes? For example ...
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CNN image classification [closed]

While training CNN with a fully connected layer for image classification, isn't training everything at once the problem? For example, we want to classify dogs. Somehow in the first epoch feature ...
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Machine Learning Models for Imbalanced Data Sets [closed]

I am working on a supervised machine learning problem - I have a very large (~100 million rows) historical dataset with several covariates, and I am trying to fit a model to this data that can predict ...
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Model Agnostic Meta Learning on custom data

I have been trying to train the model agnostic meta learning model on a custom dataset with 100 classes and 5 examples in each class from here The structure of my data is: ...
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How to justify the chosen neural architecture?

I had a task to implement a neural network that would carry out multiclass classification of traffic by several parameters. On the advice of colleagues, I chose the "Multilayer Perceptron" ...
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Unsupervised classification of objects based on relationships

I have size measurements of 1000 objects, measured over time. I would like to classify the objects based on the response of their size to time using unsupervised classification. For example, the size ...
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Machine Learning Models for Longitudinal Data

Recently, I had the following question about supervised classification models (e.g. random forest) for longitudinal data. Suppose I have the following data about students passing a fitness test - the ...
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How to optimize input image tensor, to best fit image classifier, for specific target class?

Assume that we got pretrained image classifier, and we want to then optimize some input image tensor for it, that for given class, the output of classifier will match. How to do this for example in ...
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ML algorithm suggestion for databases that change a lot with time after model training

I have a classification problem and I'm using a logistic regression (I tested it among other models and this one was the best). I look for information from game sites and test if a user has the ...
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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 ...? [closed]

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 ...
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Pattern recognition for live stream Time serie

I would like to submit you a problem with which I struggle. Suppose I have this kind of record over time in a dataframe: fig.1 If we zoom in a bit we see such shape: fig.2 We see that the general ...
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ML model to predict timeouts

I am new to ML and am trying to build a model to predict timeouts for a website. The website is being monitored once a minute and the data consists of a timestamp and the response time in seconds. E.g....
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How can I vectorize fictional single word (not sentence!) for classification?

I am working on fictional single words (names) generator that have to sound like words from a given sample. I have the generator up and running that gives reasonable words 70% of time. I thought of ...
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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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Overfitting problem - poor performance on test data

I'm facing the problem of overfitting and I can't deal with it - I tried experimenting with optimizer, but nothing seems appropriate. My model has extremely poor performance on testing data and the ...
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How can my RNN get way better results than my ANN [closed]

So, I'm using the same dataset in both models but my RNN gets a 95% accuracy and my ANN gets 52%. It is a time series, binary classification problem, and I know that RNN is better than ANN for time ...
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Do the values over 0.5 mean my model classified the data as a "1" label and vice versa?

I am doing binary classification using an LSTM and my output layer is 1 neuron with a sigmoid function. My labels are either 0 or 1. ...
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What kind of features does each node have as an input graph to a graph neural network?

What kind of features does each node have as an input graph to a graph neural network? For example, we want to do image classification with GNN, what are the features of each pixel? Or if anyone could ...
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Is there a shared minimalist taxonomy of the fields of AI?

Is there a reasonably accepted/shared view on how to minimally classify the various fields of AI? There are hundreds of techniques and I have not been able to find a shared exhaustive classification ...
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How to convert prediction probabilities of 2D images (initially 3D image) to 3D image predictions?

Classification: binary Model: CNN (ResNet50V2) During our research we've had 91x109x91 images (3-dimensional). We've used 2D CNN to train and evaluate our images and make predictions on labelled cases,...
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What will happen if I concatenate one-hot-encoded categorical features along with continuous numerical features?

Here is one row from my data: H 7.042 5.781 5.399 -9.118 5.488 7.470 The first column is a categorical class. The rest of them are continuous numerical ...
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Focal Loss vs Weighted Cross Entropy Loss

Weighted Focal Loss is defined like so $FL(p_t) = -\alpha_t log(p_t) (1-p_t)^\gamma $ Whereas weighted Cross Entropy Loss is defined like so $CE(p_t) = -\alpha_t log(p_t)$ Some blog posts try to ...
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Detecting cheats visually using AI

I really like to play my favorite 3D shooter game online. Unfortunately, it is really old and cheat protection isn't really common there, but cheaters are! It is very frustrating, because it really ...
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Multiclass Ensemble Methods with weak classifiers under 50%

Normally, when using an ensemble method, such as baggin or boosting, in binary classification, there is a reqauirment that each weak classifier have accuracy better than 50%. In the multiclass ...
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Are Neural Networks only really useful for Image Classification?

Let's say I wanted to predict whether someone was Male or Female based on what they answered to certain survey questions. I can see something like a Random Forest or KNN being useful here, but is ...
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Training a regression model on a set of values in 0-1 range to give 0-1 continual values

I have a textual dataset that has a set of real numbers as labels: L={0.0, 0.33, 0.5, 0.75, 1.0}, and I have a model that takes the text as input and has a Sigmoid output. If I train the model on this ...
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Yolo objectness parameter (called p0) vs probability parameters as explained by Joseph Redmon

I have been watching Joseph Redmon (developer of YOLOv3) lecture about YOLO from 45:04 where he explains why he needs both predictions: "objectness" called P0 VS class probabilities called ...
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Is there a standard term for the following flaw in the data?

I wonder if following characteristic of data has some standard "professional" or scientific term associated with it. Let's assume that I have a set of dog/cat images labeled 0 for a cat and ...
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Test accuracy go down after decreasing learning rate

My project include classification of images into several classes. I'm having a strange issue related to adding mixup augmentation. The accuracy of the training set and the validation set keep rising ...
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Impact of imbalanced dataset on CNN model performance

I trained a 1D CNN model to model bacterial plate count based on time series data of water temperature. Bacterial place count is numerical, based on which I created two category variables, namely &...
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Is a Transformer a good choice for multivariate signal classification?

I am working on a problem regarding the multi-classification of multivariate time signals. So I have multiple signals and try to train an algorithm on them. My current approach is to build a neural ...
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How to force/instruct CNN to learn specific features?

Let's say I have a CNN that classifies shirts. And let's say that it performs poorly on shirts that have horizontal stripes. How would I force network to put more emphasis on shirts with horizontal ...
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Is categorical cross entropy better than binary cross entropy for imbalanced binary classification problems

I am training a NN model. The data is highly imbalanced (3% for positive labels), and I have not resampled more true classes in the training set. The model performs much better when categorical cross-...
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How do I apply non-max suppression for 2-classes problems?

I have basic knowledge about non-max suppression and I know how it works for multiple classes, but what if I want to get a prediction for two classification problems? I give you an example. So I have ...
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What model to train to restore MNIST test dataset

I came across this problem, and am not sure where to start. What model would work best for this problem and why? Imagine the digits in the test set of the MNIST dataset (http://yann.lecun.com/exdb/...
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If the model always underfits, do I really need a larger model?

I train my neural network on random points generated for a data set that theoretically consists of approximately $1.8 * 10^{39}$ elements. I sample (generate) tens of thousands of random points on ...
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How can a neural network distinguish a rotated 6 and 9 digits?

Rotated MNIST is a popular dataset for benchmarking models equivariant to rotations on $\mathbb{R}^2$, described by $SO(2)$ group or its discrete subgroups like $\mathbb{Z}^{n}$: Group equivariant ...
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Comparing large numbers of images to find outliers

There are many methods you can use to compare two images in ML (Siamese NN, CNNs, Ect.) What I cannot figure out is comparing a large number of images (Without Retraining) to find images of a ...
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What to predict in a limited transaction dataset?

I have been given a task with a real transaction dataset. The task is to predict something using either logistic regression or simple binary classification. The columns are as follow: Transaction ID ...
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Is there a way to update the neural network to fit the new data without the time required for retraining?

I built a basic neural network in MATLAB. The neural network classifies points on the X-Y axis system into two classes (0 and 1). (I try to get the function that represents a shape from this photo) ...
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Why is/can node classification (graph machine learning) be semi-supervised while graph classification is supervised?

I was reading about different graph machine learning tasks in this book (Chapter 1) here and to learn about node classification and graph classification tasks. Then I looked at this paper here, which ...
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Multi label classification on non binary labels with pytorch

I am working on a project consisting of medical images and a huge dataset of multi-label and non-binary labels/outcomes ( sex, blood pressure, age and 40 more ). Would be the best approach to hard ...
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Should I train my network for classification on samples whose ground truth label is ambiguous?

Imagine that I am training a model to classify handwritten digits. Suppose there are some bad quality images that could be classified by a human as either 0 or 8, 1 or 7 or other commonly ...
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Identify Merchants from Transaction Dataset

I have a transaction dataset, each transaction is in an unstructured format. The objective is to identify merchant from each transaction. If we look it from NER point of view, there would be problem ...
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Is it normal that the values of the LogSoftmax function are very large negative numbers? [closed]

I have trained a classification network with PyTorch lightning where my training step looks like below: ...
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Algorithm/methodology for JSON document classification/prediction

I would like to build a system (or use an existing one, if it exists) that learns and classifies JSON documents (objects) into categories. The input JSON objects will have a few standard properties ...
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Is having near-duplicates in a training dataset a bad thing?

I am making a labeled dataset of images from web streams for a CNN classification. Pictures from the same stream are quite similar as far as background, but slightly different as far as the main ...
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What should the value of $ρ$ in the $w(n+1) = w(n) + \rho*\text{error}(i)x(i)$ formula of Least Mean Squares be?

I am trying to better understand the Least Mean Squares algorithm, in order to implement it programmatically. If we consider its weight updating formula $$w(n+1) = w(n) + \rho * \text{error}(i)x(i),$$ ...
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