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

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"NAs introduced by coercion" in One-Class SVM using R [closed]

I am trying to perform a one-class SVM on my data set for anomaly detection. I keep getting a warning that "NAs introduced by coercion", which then does not allow me to fit my one-class SVM ...
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One-class SVM with single dimension and polynomial kernel

Context: I'm studying anomaly detection without prior experience in machine learning, although I'm a senior web developer. This article talks about the kernel trick and gives this example with single ...
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How can I make sense of alpha values obtained from scikit-learn OC-SVM?

I am building a ML model that uses the OC-SVM for anomaly detection. For our cost function we require the alphas obtained from the OC-SVM. We use the OC-SVM of scikit-learn, which I assume is based on ...
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Should I scale my data before a Cartesian-to-spherical conversion?

If I have three features, should I scale them before converting them to a spherical coordinate system? I have been working on a ternary classification problem. My data is high-dimensional, so I've ...
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Why are odd-degreed polynomial kernels slower than those with even degrees for SVM?

I have been using one-class support vector classifiers to extract features for multinomial classification. I noticed that fitting time is much longer when the degree of the polynomial kernel is odd. ...
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One class SVM and centered data

I understand that the one class SVM try to separate the normal training data point from the origin. My guess is that, if we centered the data in a normalisation step, the OCSMV will works poorly since ...
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Fitting a classifier with aymmetric loss and a cumulative objective

I'm looking at classification problems of the form: $$ \max_{w} \sum_{i} y_i * (2 * sign(w^T x_i + b) - 1) $$ I have a set of observations $x_i \in \mathbb{R^n}$ with corresponding values $y_i \in \...
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Lots of unlabeled data and small set of labelled data of one class [closed]

Does anyone have suggestions for specific algorithm or implementation for labeled data of only one class and unlabeled data that can be from either classes? And I'm unsure what is the proportion of ...
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How should I construct a binary classifier for small set of positive data and million of unlabeled data?

Does anyone have suggestions for specific algorithm or implementation for labeled data of only one class and unlabeled data that can be from either classes? And I'm unsure what is the proportion of ...
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Generating data for one-class dataset

In case I have a dataset that have only one class unlabeled (benign), could you please list some algorithms/papers that are used to generate complementary data (malignant) based on benign data only? I ...
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One Class Classifier for balanced binary dataset

Can I use one class classifier for the balanced binary dataset? For example, consider a text sentiment analysis dataset in which a number of positive and negative samples are equal Can I use one class ...
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Why do distances to hyperplane increase with more training samples in a One-Class SVM?

I am using a One-Class SVM from for anomaly detection. I observe that the distance of classified samples increases roughly proportional with the number of training samples. This is true for inliers ...
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1 answer
494 views

Anomaly detection using Mahalanobis distance

I am using Mahalanobis distance to identify outliers. I am training using kind of one class classification,by training only on positive samples and trying to predict negative samples using distance ...
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2 votes
2 answers
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what would be a recommended division of train and test data for one class SVM?

I have checked the following one class SVM classification in R that was posted in this thread: https://stackoverflow.com/questions/27375517/one-class-classification-with-svm-in-r In this program the ...
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One Class Classification for recommending perfect bouquet of flowers

For my university project I have the following problem and I am wondering what might be the best approach to solve it: Say, I want to generate the best bouquet of flowers as a florist based on ...
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how to do the hyper parameter tunning for one class svm in r programming?

x is input (single column) tuned <- tune.svm(x=x, y =NULL, data=x, type= 'one-classification', tunecontrol = tune.control(sampling = "fix")) For this I am ...
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Kernel selection for one-class SVM learning

Has anyone seen compelling research on kernel selection for one-class SVM learning? I've not tracked this work in some time and am wondering if there's new work I've missed, particularly from the ...
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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 ...
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3 votes
2 answers
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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 ...
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Is it OK to have only a single class labels in test data for prediction with one-class-svm?

I have a data which has only a single class, namely, '0'. There is no 'not 0' class. The one-class SVM model was trained on a <...
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1 vote
1 answer
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What are the anomalies/fault/outliers detection algorithms

I'm working on a weather application that uses data coming from multiple sensors in real time (the data is time series), i've made an anomalies detection model using One Class Support Vector Machines, ...
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1 vote
1 answer
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software for one class classification with a Bayesian Network

I'm looking for a software package that would allow to do a one class classification with a Bayesian Network (anomaly detection). I was planning to use bnlearn but so far I'm unable to find out if ...
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Why setting SVDD's C-parameter to $> 1$ does not affect the result?

Why setting $C>1$ does not affect the result (compared to $C=1$) according to: https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/#libsvm_for_svdd_and_finding_the_smallest_sphere_containing_all_data ...
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Can One-Class SVM be used for outlier detection?

According to my readings (Support Vector Method for Novelty Detection, for instance), One-Class SVM can be used for novelty detection only. The purpose of the $\nu$ parameter is to defined the maximum ...
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Where does "ρ" come from in the primary objective function ?

I'm trying to fully understand the primary objective of one-class SVM function. This function is defined in paragraph 3.2 of Enhancing One-class Support Vector Machines for Unsupervised Anomaly ...
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6 votes
1 answer
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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 ...
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Anomaly detection in Text Classification

I have built a text classifier using OneClassSVM. I have the training set which corresponds to only one label i.e("Yes") and I don't have the other("NO") label data. My task is to build a classifier ...
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2 votes
2 answers
695 views

How to choose a method for binary classifier based on only positive and unlabelled examples?

I need to build a binary classifier with machine learning, as I fail to manually choose a combination of features to achieve minimal fraction of false positives. What is best practice for choosing a ...
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1 vote
1 answer
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Anomaly/Outlier detection based on Windows event security logs (logons) using Machine Learning(in Python) [closed]

I am trying to solve the problem of finding anomalies/outliers using event security logs of an individual system. Please find the details below: Problem Statement: Find anomalies/outliers using event ...
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6 votes
1 answer
1k views

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 ...
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1 vote
1 answer
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nu parameter in one-class SVM with linear kernel

I have made a one-class SVM model using the Linear kernel. I trained my model with 100000 positive examples, each one having a vector of 59 dimensions. The examples come from a public dataset, which ...
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Normalising features for One Class SVM

I have my feature space that is Year Month Day Hour Minute Second Lane Direction Speed Flag A sample vector would look like: ...
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One Class SVM for Time Series data

I am trying to use an OCSVM for my time series data which looks like this: ...
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3 votes
1 answer
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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 ...
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1 vote
1 answer
834 views

Unsupervised learning methods on unlabeled data?

I'm facing with a challenge of unsupervised classification of unlabeled data. The case is, I have circa 1.2 million vehicle warranty claims, and must develop a classification model to tell whether ...
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1 answer
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One-class SVM: "training set vs. origin" logic

first of all, I apologize about asking this question again since a similar one was posted recently; I had to repost it since I still don't understand the answer and I had no other way to interact with ...
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109 views

One-class svm with given true positive rate

Is it always possible to find a one-class SVM with given true positive rate (TPR)? I used 1-D grid search with cross-validation to find the width parameter of RBF kernel with .90 TPR. The closest ...
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3 votes
3 answers
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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 ...
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One Class Classification on high dimensional space

I want to solve OCC(one class classification) on images, the input would be an image, the output is if the image belong to the class, and I extract the image feature from a deep neural work, the ...
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3 votes
3 answers
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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 ...
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Machine Learning algorithm for a lack of domain data?

When a user searches for an item to purchase on a retail website they can input some features of their desired item to narrow down their search results. This produces a list of items that match their ...
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How to use Probability (-b1) for one-class classification using LibSVM?

I need some information concerning the LibSVM one-class classification. I use -b1 for two-class classification in SvmTrain and my outputs are prob values and prob labels. I want to use the similar ...
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415 views

Outlier Detection giving almost all training points as outliers

I am trying to run an outlier detection algorithm using python and I have used OneClassSVM and Isolation Forest on a dataset of about 30 points with 5 outliers. I have trained on the 25 points and ...
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-1 votes
1 answer
179 views

Using LibSVM for One-Class-Classification

Why do the same instances, in training and testing, get classified as unknown in LibSVM? I'm using the linear kernel function nu=0.1, gamma=0.1 Here is the instance that is in both the training and ...
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1 vote
0 answers
331 views

One Class classification using Kernel Density Estimate

I have a dataset of customers who belong to one-class (say C1). I have another data set of customers (C2) and I need to find out how similar are these to customers in C1. This is what I have tried so ...
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3 votes
1 answer
643 views

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 ...
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1 vote
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Classification of a single group?

This might be completely unfeasible or obvious, but I wanted to see if anyone has come across a similar problem. Typical classification methods (decision tree, random forest, etc) require at least two ...
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2 votes
1 answer
6k views

Best way to train one-class SVM

Let`s say I have training data which contains 10 classes and have build a classifier using this data. When applying this classifier in real life it may encounter examples not belong to the classes ...
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7 votes
2 answers
10k views

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 ...
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1 vote
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What is an appropriate metric to optimize for when comparing different models for one-class classification?

Say I have a set of 100 positive and 1,000 unlabeled points. Among those unlabeled, some are presumably similar enough to the positives that they should belong to the positive class. Yet, if I ...
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