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 to implement an “unknown” class in multi-class classification with neural networks?

For example, I need to detect classes for MNIST data. But I want to have not 10 classes for digits, but also I want to have 11th class "not a digit", so that any letter, any other type of ...
2
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2answers
146 views

Difference between training accuracy and calculating accuracy with class prediction

I have trained my neural network with a dataset of 11200 images, and its validation accuracy was 96%. I saved my model and load its weights to the same neural network. I chose 738 images of my dataset ...
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2answers
78 views

What does the depth of a decision tree depend on?

In these notes, we have the following statement The depth of a learned decision tree can be larger than the number of training examples used to create the tree This statement is false, according to ...
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2answers
87 views

If the training data are linearly separable, which of the following $L(w)$ has less optimum answer for $w$, when $y = w^Tx$?

I'm studying machine learning and I came into a challenging question. The answer is 2. But based on my ML notes, all of them are true. Where are the wrong points?
2
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1answer
268 views

How to detect multiple playing cards of the same class with a neural network?

I want to train an AI to detect the class (i.e. suit and rank) of playing cards. Playing cards from different decks may use slightly different shapes or colors to represent these attributes, and I ...
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0answers
16 views

In few-shot classification, should I use my custom dataset as the validation dataset and mini-ImageNet as the training dataset?

I am new to few-shot learning, and I wanted to get a hands-on understanding of it, using Reptile algorithm, applied to my custom dataset. My custom dataset has 30 categories, with 5 images per ...
3
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1answer
79 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
68 views

How are temporal links made between following sequences in RNN?

Say I use an RNN, whatever is the cell's type, to perform time series classification. It can thus be seen as sequence classification. The time series is split into random, equal size, overlapping ...
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26 views

Multivariate time-series classification with many variables

I am attempting to use time-series classification algorithms for fraud detection applications. I have came across several works in the literature that propose novel techniques for multivariate time-...
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0answers
75 views

Why is the margin attained with $\Phi=\left[2 x, 2 x^{2}\right]^{T}$ greater than the margin attained with $\Phi=\left[x, x^{2}\right]^{T}$?

I am trying to understand the solution to part 4 of problem 3 from the midterm exam 6.867 Machine learning: Mid-term exam (October 15, 2003). For reproducibility, here is problem 3. We consider here ...
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1answer
32 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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1answer
62 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 ...
3
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1answer
63 views

What is meant by “the number of examples is reduced”, and why is this the case?

I am currently studying the paper Learning and Evaluating Classifiers under Sample Selection Bias by Bianca Zadrozny. In section 3.2. Logistic Regression, the author says the following: 3.2. Logistic ...
2
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1answer
42 views

When could a linear discriminant give excellent or possibly even the optimal classification accuracy?

I am actually reading the linear classification. There is a question in the question set behind the chapter in the book as follows: Sketch two multimodal distributions for which a linear discriminant ...
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1answer
37 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 ...
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2answers
57 views

Can training a model on a dataset composed by real images and drawings hurt the training process of a real-world application model?

I'm training a multi-label classifier that's supposed to be tested on underwater images. I'm wondering if feeding the model drawings of a certain class plus real images can affect the results badly. ...
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0answers
24 views

The last target name is missed in the test set

I am training a neural network with a dataset that has 51 classes and 6766 data in it. I used 80% for the training set, 10% for validation, and 10% for the test. After training I got confusion matrix ...
2
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1answer
42 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 ...
0
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1answer
37 views

How to do early classification of time series event with small dataset?

I would like to build a real-time binary classifier that can predict an event of interest that is occurring as soon as it starts. These are electromyographic signals, and the event classification ...
1
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1answer
41 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 ...
2
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0answers
40 views

How does the support vector machine constraint imply that sample selection bias will not systematically affect the output of the optimisation?

I am currently studying the paper Learning and Evaluating Classifiers under Sample Selection Bias by Bianca Zadrozny. In section 3.4. Support vector machines, the author says the following: 3.4. ...
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0answers
20 views

Network structure of generative model for classification

I'm trying to model a generative model for classification problem, especially aiming to solve an imbalanced data problem. However, I couldn't get intuitive understanding for generative classifier in ...
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0answers
17 views

Is the PR AUC invariant under label flip?

The ROC-AUC curve is invariant under a flip of the labels. I don't know if it's a famous result, so I will give the proof below. My question is if the PR-AUC curve also has this property. I have not ...
2
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1answer
99 views

Why do I get small probabilities when implementing a multinomial naive Bayes text classification model?

When applying multinomial Naive Bayes text classification, I get very small probabilities (around $10e^{-48}$), so there's no way for me to know which classes are valid predictions and which ones are ...
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0answers
14 views

Can we encode categories binarily in a classification task using neurons outputs as consecutive bits?

Let's say, that we have a simple neural network as the one depicted below: The goal of this NN is to classify inputs into two separate categories. Usualy, each neuron would correspond to one category,...
3
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1answer
454 views

Alternative to sliding window neural network (was: Object detect (or) image classification at specific locations in the frame)

Recent advances in Deeplearning and dedicated hardware has made it possible to detect images with a much better accuracy than ever. Neural networks are the gold standard for computer vision ...
3
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2answers
93 views

Which online machine learning technique to use for multi-class classification problem with multiple inputs?

I have the following problem. We have $4$ separate discrete inputs, which can take any integer value between $-63$ and $63$. The output is also supposed to be a discrete value between $-63$ and $63$. ...
2
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1answer
102 views

Is there a mathematical theory behind why MLP can classify handwritten digits?

I'm trying to really understand how multi-layer perceptrons work. I want to prove mathematically that MLP's can classify handwritten digits. The only thing I really have is that each perceptron can ...
2
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0answers
22 views

Literature on the advantages of using an auto-encoder for classification

Given a supervised problem with X, y input pairs, one can do two things for obtaining the function f that maps X with y with Neural Networks (and in general in machine learning): Deploy directly a ...
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2answers
84 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 ...
3
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1answer
4k views

How to calculate the entropy in the ID3 decision tree algorithm?

Here is the definition of the entropy $$H(S)=-\sum_{x \in X} p(x) \log _{2} p(x)$$ Wikipedia's description of entropy breaks down the formula, but I still don't know how to determine the values of $X$,...
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1answer
50 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 ...
2
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0answers
17 views

Image classification - Need method to classify “unknown” objects as “trash” (3D objects)

We have an image classifier that was built using CNN with faster R-CNN and Yolov5. It is designated to run on 3D objects. All of those objects have similar "features" structure, but the ...
2
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1answer
111 views

Why is this ResNet50 misclassifying objects?

I'm new to Deep Learning, and I have some conceptual problems. I followed a simple tutorial here, and trained a model in Keras to do image classification on 10 classes of logos. I prepared 10 classes ...
1
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1answer
43 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....
3
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1answer
64 views

Is this referring to the true underlying distribution, or the distribution of our sample?

I am currently studying the paper Learning and Evaluating Classifiers under Sample Selection Bias by Bianca Zadrozny. In the introduction, the author says the following: One of the most common ...
1
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1answer
27 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
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1answer
96 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 ...
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0answers
31 views

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 ...
2
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1answer
108 views

How do I check that the combination of these models is good?

I've selected more than 10 discriminative (classification) models, each wrapped with a BaggingClassifier object, optimized with a ...
2
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1answer
425 views

Can ConvNets be used for real-time object recognition from video feed?

Convolutional neural network are leading type of feed-forward artificial neural network for image recognition. Can they be used for real-time image recognition for videos (frame by frame), or it takes ...
2
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0answers
24 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 ...
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0answers
39 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 ...
1
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1answer
46 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
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1answer
52 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? ...
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0answers
20 views

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 ...
5
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1answer
959 views

What is the difference between imitation learning and classification done by experts?

In short, imitation learning means learning from the experts. Suppose I have a dataset with labels based on the actions of experts. I use a simple binary classifier algorithm to assess whether it is ...
2
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1answer
54 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....
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0answers
16 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 ...

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