Statistical Analysis Stack Exchange
Statistical Analysis Stack Exchange

Questions tagged [one-class]

One-class classification, also known as unary classification, tries to identify objects of a specific class amongst all objects, by learning from a training set containing only the objects of that class. This is different from and more difficult than the traditional classification problem, which tries to distinguish between two or more classes with the training set containing objects from all the classes. PU (positive unlabelled) learning is a special case

As defined by Wikipedia

one-class classification, also known as unary classification, tries to identify objects of a specific class amongst all objects, by learning from a training set containing only the objects of that class. This is different from and more difficult than the traditional classification problem, which tries to distinguish between two or more classes with the training set containing objects from all the classes.

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Classifier for only one class

In a simple classification, we have two classes: class-0 and class-1. In some data I only have values for class-1, so none for class-0. Now I am thinking about making a model to model the data for class-1. So, when new data come, this model is…
Big Data Lover
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Bayesian networks for one-class classification

From the definition of one-class classification in wikipedia: In machine learning, one-class classification, also known as unary classification or class-modelling, tries to identify objects of a specific class amongst all objects, by learning…
JEquihua
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GANS: Using Discriminator for prediction

In the past few years, GANs have been a hot topic and a lot of papers are being published every year regarding GANs. But I always see that either the results of the generator are being shown (sample pictures or anything else generated by the…
Ramesh9874
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What if I train a classifier with only positive example?

I am interested to know what happens if I have enough positive examples and I train a Classifier with those but no negative examples were provided. Since I am interested to find outliers (anything other than positive class), will this model work?…
N. F.
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What are the classification models that work on single-class classification problems?

Beside SVM, what are the classification models that can be trained by a dataset of only positive training examples? and which of these models are generally known to perform better in such cases? UPDATE: I mean problems that are described by the…
PatternRecognition
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Why we need single class classification?

I have started learning classification in machine learning. I face two terminologies, one is "single class classification" and a the other is "binary class classification". I am confused about when to use single class classification and when to use…
Argha
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How can I create a neural network that can recognize objects without having data for objects that aren't in the classification set?

I have a data set of 10,000 images of 5 different recycling items. The goal of my neural network is to tell me if an item is recyclable or not. The problem is that I only have data for the 5 different classifications (soda can, crushed soda can,…
Anthony
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Parameter optimization in one-class SVM of LibSVM

I am new to machine learning and SVMs. I have a general question regarding the optimization of parameters in one-class SVM in libsvm in R. I found similar posts but yet not conclusive answer. Can someone tell me, do I need to optimize both c (cost)…
Thanos
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Metrics for one-class classification

How do you calculate precision and recall in one class classification? In other words in one class classification, we just have TP(True Positive) and FN(False Negative). Which metrics we should use for these type of classification?
Sara Nikdel
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Is there a metric for data where only true positives are labeled (no true negatives)?

Let's say I have a dataset where each item is labeled with either (1) true positive or (2) unknown (could be true positive, could be true negative). It seems like if there are only true positives labeled, the only penalty you can impose is if…
hume
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How does a one-class SVM model work?

I am working on a problem involving outliers detection and I found that it was possible to perform this using one-class SVM. I have been googling it and reading some blogs and papers, but I have a doubt it seems not to be solved elsewhere. As far as…
Álvaro Méndez Civieta
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Why One class SVM seperate from the origin

I don't understand what is the intuition behind the idea of finding a hyperplane that separate the training data from the origin if the feature space. To me it would be more intuitive to create a boundary around the positive class from all direction…
Dr.nina
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one class (positive and unlabeled) classification R package

I have two data sets: one for "good old customers" and a newer one with "new customers". My need is to "predict" which ones of the new customers would be rated as "potentially good customers" using the good customers data and variables. So, a simple…
jomaweb
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One-class KNN for Quality Control

I've come across this paper https://uta-ir.tdl.org/uta-ir/bitstream/handle/10106/1827/Sukchotrat_uta_2502D_10083.pdf?sequence=1&isAllowed=y] where it is described a k-Nearest Neighbors Data Description (kNNDD)-Based Control Chart. (pag 45) First,…
momomi
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How to set $\nu$ parameter for one-class SVM?

I am trying to perform one-class SVM for novelty detection, so I use cross-validation to find the best $\nu$ parameter, but I found that usually I got a big parameter $\nu$, resulting in a big false positive rate. How to set and find the $\nu$…
Mark.M
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