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, .

124 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
1
vote
0answers
27 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 ...
1
vote
0answers
26 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 ...
1
vote
0answers
24 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 ...
1
vote
0answers
26 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 ...
1
vote
1answer
31 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 ...
1
vote
0answers
33 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 ...
1
vote
0answers
25 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, ...
1
vote
0answers
13 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 ...
1
vote
0answers
22 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 ...
1
vote
0answers
12 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 ...
1
vote
0answers
19 views

Is it okay to have wide variations within one of the classes for binary classification tasks?

Say I am using a convolutional network to classify pictures of my face versus anyone else's face in the world. So let's take 10000 pictures of me, and 10000 pictures of other people. And let's do ...
1
vote
0answers
21 views

Model unfit for some part of spiral data despite low error

I'm current testing a model for spiral data. After 500 epoches, loss is 0.04 but the result is still unmatch with some part of the training data. (bottom left) The model has 2 hidden tanh x 16 units ...
1
vote
0answers
19 views

How to update edge features in a graph using a loss function?

Given a directed, edge attributed graph G, where the edge attribute is a probability value, and a particular node N (with binary features f1 and f2) in G, the algorithm that I want to implement is as ...
1
vote
0answers
31 views

Is it possible to do token classification using a model such as GPT-2?

I am trying to use PyTorch's transformers as a part of a research project to do sentiment analysis of several types of review data (laptop and restaurant). To do this, my team is taking a token-...
1
vote
1answer
35 views

How to calculate the confidence of a classifier's output?

I'm training a classifier and I want to collect incorrect outputs for human to double check. the output of the classifier is a vector of probabilities for corresponding classes. for example, [0.9,0....
1
vote
1answer
42 views

Hand-Signs Recognition using Deep Learning Convolutional Neural Networks

I am developing a CNN model to recognize 24 hand-signs of American Sign Language. I have 2500 Images/hand-sign. The data split is: Training = 1250 Images/hand-sign Validation = 625 Images/hand-sign ...
1
vote
0answers
19 views

Post-classification after inference

I designed a fire detection using Deep Learning based classification approach. In my training dataset, I have both fire and fire smokes are supposed to be detected (all under "fire"; mostly real fires ...
1
vote
0answers
31 views

What's the mathematical relationship between number of trainable parameters and size of training set?

Let's say that I have a pre-trained model where the training set used to pretrain the model is very different from my training set. Let's say I unfreeze layers that have X trainable parameters. What ...
1
vote
0answers
23 views

Variable binning for NN

I come from a background of scorecard development using logistic regression. Steps involved there are: 1. binning of continuous variables into intervals (eg age can be binned into 10-15 years, 15-20 ...
1
vote
0answers
32 views

Outliers detection problem in neural networks

Assuming we have big m x n input dataset with m x 1 output vector. It's a classification problem with only two possible values: either 1 or 0. Now the problem is that almost all elements of the output ...
1
vote
0answers
22 views

How to train image segmentation task with only one class?

Is there a neural network that has architecture optimizations for segmenting only one class (object and background)? I have tried U-net but it is not providing good enough results. I am wondering if ...
1
vote
0answers
36 views

Relationship between model complexity (depth) and dataset size

I'm new to deep learning. I was wondering what's the relationship between a deep model complexity (e.g. total number of parameters, or depth) and the dataset size? Assuming I want to do a binary ...
1
vote
0answers
13 views

Is there an algorithm for “contextual recognition” with probabilities?

Example 1 An object is composed of 3 sub-objects. Object 1: 90% looks like an eye 10% looks like a wheel Object 2: 50% looks like an eye 50% looks like a wheel Object 3: 90% looks like a mouth 10% ...
1
vote
0answers
30 views

The membership function of Consequents (Outputs) in Fuzzy classifier

The problem in Iris data is to classify three species of iris (setosa, versicolor and virginica) by four-dimensional attribute vectors consisting of sepal length (x1) sepal width (x2) petal length (...
1
vote
0answers
28 views

How to change the architecture of my simple sequential model

I'm new to Deep Learning with Keras. With some tutorials online for cat vs non-cat classification, I was able to compile this simple architecture for my own ...
1
vote
0answers
59 views

Focal loss for imbalanced multi class classification in Pytorch

I want an example code for Focal loss in PyTorch for a model with three class prediction. My model outputs 3 probabilities. ...
1
vote
0answers
16 views

CNN multi output scores and evaluation

I am building a CNN with two outputs. I still have to put time in the network itself, but I was trying to get a good evaluation/classification report of the results. My code is the following: ...
1
vote
0answers
10 views

Is there any time-varying directed graph dataset?

I am interested in the node classification task for graph data. So far,I've tried it with the Cora dataset, but it is an undirected graph and has word attributes as features. I want to extend this ...
1
vote
1answer
52 views

How to use a deep learning network on new data-set?

I am trying to use a network for classification. This network works very well on the author's example data, but doesn't work on new data. Currently, I am using the popular EEG Motor Movement/Imagery ...
1
vote
0answers
25 views

Trying to separate spiral data with neural network, learning tensorflow

I am learning how to use tensorflow without keras, just to make sure I understand tensorflow directly. I created a spiral-looking datasets with 100 points of each class (200 total), and I created a ...
1
vote
1answer
69 views

Can maximum likelihood be used as a classifier?

I am confused in understanding the maximum likelihood as a classifier. I know what is Bayesian network and I know that ML is used for estimating the parameters of models. Also, I read that there are ...
1
vote
0answers
16 views

Probabilistic classification - normalize results

I have a probabilistic classifier that produces a distribution over my 3 classes - C1, C2, C3. I want to compare some new points I'm classifying to each other, to see which one is the best fit for a ...
1
vote
0answers
66 views

Is this a classification problem?

I’m not really sure which machine learning approach is best for my problem at hand. I work in an engineering company that designs and builds different kinds of ships. In my particular job, I collect ...
1
vote
1answer
35 views

Obtain the most important input data for binary classification on a neural network

I have a simple neural network for a binary classification. Input features include: age, sex, economic_situation, illness, disability, etc. Output is simply 1 and 0 I would like to order the features ...
1
vote
0answers
14 views

Binary annotations on large, heterogenous images

I'm working on a deep learning project and have encountered a problem. The images that I'm using are very large and extremely detailed. They also contain a huge amount of necessary visual information, ...
1
vote
1answer
81 views

How can I stabilise a recurrent neural network used for binary classification?

I’m looking for some help with my neural network. I’m working on a binary classification on a recurrent neural network that predicts stock movements (up and down) Let’s say I’m studying Eur/Usd, I’m ...
1
vote
0answers
13 views

Training Haar Cascade model with grey vs color images

Most examples if not all, are models that have been trained with images that are turned grey. Does this mean that models only detect edges? Why wouldnt you want to keep color so that model could learn ...
1
vote
0answers
23 views

Would this NN for my chip outputs work?

I'm a grad student from EE. So, basically, there's an electrical circuit that is supposed to output "0" or "1" by exactly 50 to 50 chance. It generates a number of big arrays of 0s and 1s, each of ...
1
vote
0answers
26 views

Evaluation metrics multi-class classification (ROC- PR curves)

Facing with a multi-class classification task, my question is: are ROC and Precision-Recall (One-vs-All-Rest) curves useful to evaluate and visualize the performance of a model? or Confusion ...
1
vote
0answers
27 views

Classification of classes within meta-classes

TLTR: I'm developing a CNN for a classification task. The data contains multiple classes some of which are very similar to each other and I know these meta-classes. In such a situation is it a good ...
1
vote
0answers
48 views

Why validation performance is unstable for my LSTM based model (labelling problems)?

I have trained a recurrent neural network based on 1 stack of LSTM cells. I use it to solve a classification problem. The RNN cell has 48 hidden states. The output of the last unfolded LSTM cell is ...
1
vote
0answers
86 views

Siamese Network for unknown object

I am currently trying to create a One-Shot network using the Siamese architecture for an object that isn't a face. My problem is, in normal Face Recognition the detecting gadget (e.g. Smartphone) ...
1
vote
0answers
73 views

Dialects classification using deep learning

Dialects differ a lot between cities in my country, Syria. People sometimes express themselves using different local phrases and idioms which refer to the same topic. So, I came up with the idea of ...
1
vote
0answers
31 views

identifying pattern in datasets

i am new to machine learning. i'm trying to identify driving pattern through accelerometer and gyroscope sensor. i have been collecting the data of both the sensors and have been storing them in .csv ...
1
vote
1answer
20 views

Using convnet to classify language of text contained in images

I hope this question is not too broad or general. I have a very large set of images all of which contain text (some have more, some less). All of them have been tagged as containing, say, English text ...
1
vote
0answers
28 views

Any guidance on learning rate / batch size for noisy data (high Bayes error rate)?

Is there any guidance available for training on very noisy data, when Bayes error rate (lowest possible error rate for any classifier) is high? For example, I wonder if deliberately (not due to memory ...
1
vote
0answers
47 views

Bubble Chamber Image Analysis Using Neural Network

I have a data analysis problem that I can reduce to one similar to analyzing the trajectories in the images below. These images show the tracks of subatomic particles interacting in a bubble chamber. ...
1
vote
1answer
56 views

Relationship between input range and channel means, standard deviations for CNNs

So, I'm using a pretrained pnasnet5large model to do some image classification (https://github.com/Cadene/pretrained-models.pytorch/blob/master/pretrainedmodels/models/pnasnet.py) In the file, it ...
1
vote
0answers
62 views

Machine learning approach to facial recognition

First of all I'm very new to the field. Maybe my question is a bit too naive or even trivial... I'm currently trying to understand how can I go about recognizing different faces. Here is what I ...
1
vote
0answers
16 views

Merge one label with one information for classification problem or multi-label classification

I want to build a model to support decision making in order to propose or not loan insurance to clients. Because sometimes clients asking loan and loan insurance have less chance to have their loan ...