libsvm
E426672
machine learning library
open-source software
software library
support vector machine implementation
libsvm is a widely used open-source library that implements Support Vector Machines for classification, regression, and related machine learning tasks.
All labels observed (1)
| Label | Occurrences |
|---|---|
| libsvm canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4277244 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: libsvm Context triple: [SVC, optimizationSolver, libsvm]
-
A.
scikit-learn
scikit-learn is a widely used open-source Python library that provides efficient tools for data mining, data analysis, and implementing a broad range of machine learning algorithms.
-
B.
LogisticRegression
LogisticRegression is a scikit-learn machine learning estimator that models the probability of class membership using a linear decision boundary with logistic (sigmoid) or related link functions.
-
C.
Apache Mahout
Apache Mahout is an open-source machine learning library designed to build scalable algorithms for clustering, classification, and recommendation on large datasets, often leveraging big data platforms.
-
D.
LFD
LFD is the National Rail station code for Lingfield railway station in Surrey, England.
-
E.
ML
ML is the postcode area in central Scotland that covers Motherwell and surrounding towns.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: libsvm Target entity description: libsvm is a widely used open-source library that implements Support Vector Machines for classification, regression, and related machine learning tasks.
-
A.
scikit-learn
scikit-learn is a widely used open-source Python library that provides efficient tools for data mining, data analysis, and implementing a broad range of machine learning algorithms.
-
B.
LogisticRegression
LogisticRegression is a scikit-learn machine learning estimator that models the probability of class membership using a linear decision boundary with logistic (sigmoid) or related link functions.
-
C.
Apache Mahout
Apache Mahout is an open-source machine learning library designed to build scalable algorithms for clustering, classification, and recommendation on large datasets, often leveraging big data platforms.
-
D.
LFD
LFD is the National Rail station code for Lingfield railway station in Surrey, England.
-
E.
ML
ML is the postcode area in central Scotland that covers Motherwell and surrounding towns.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
machine learning library
ⓘ
open-source software ⓘ software library ⓘ support vector machine implementation ⓘ |
| citationAuthors | Chih-Chung Chang and Chih-Jen Lin NERFINISHED ⓘ |
| citationTitle | LIBSVM: A Library for Support Vector Machines NERFINISHED ⓘ |
| developer |
Chih-Chung Chang
NERFINISHED
ⓘ
Chih-Jen Lin NERFINISHED ⓘ |
| field |
data mining
ⓘ
machine learning ⓘ |
| hasInterface |
C++
NERFINISHED
ⓘ
Java NERFINISHED ⓘ LabVIEW NERFINISHED ⓘ MATLAB NERFINISHED ⓘ Octave NERFINISHED ⓘ Perl NERFINISHED ⓘ Python NERFINISHED ⓘ R NERFINISHED ⓘ Ruby NERFINISHED ⓘ Scilab NERFINISHED ⓘ |
| implementsAlgorithm | support vector machine ⓘ |
| includesTool |
svm-predict
NERFINISHED
ⓘ
svm-scale NERFINISHED ⓘ svm-train NERFINISHED ⓘ |
| license | BSD-style license ⓘ |
| name | LIBSVM NERFINISHED ⓘ |
| origin | National Taiwan University NERFINISHED ⓘ |
| programmingLanguage | C ⓘ |
| supportsFeature |
cross-validation
ⓘ
parameter selection assistance ⓘ probability outputs ⓘ sparse data format ⓘ weighted samples ⓘ |
| supportsKernel |
linear kernel
ⓘ
polynomial kernel ⓘ precomputed kernel ⓘ radial basis function kernel ⓘ sigmoid kernel ⓘ |
| supportsOperatingSystem |
Linux
ⓘ
Windows NERFINISHED ⓘ macOS NERFINISHED ⓘ |
| supportsTask |
classification
ⓘ
multiclass classification ⓘ one-class classification ⓘ probability estimation ⓘ regression ⓘ |
| usedIn |
academic research
ⓘ
industrial applications ⓘ |
| website | https://www.csie.ntu.edu.tw/~cjlin/libsvm/ ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: libsvm Description of subject: libsvm is a widely used open-source library that implements Support Vector Machines for classification, regression, and related machine learning tasks.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.