ML-Schema: Exposing the Semantics of Machine Learning with Schemas and Ontologies

07/14/2018
by   Gustavo Correa Publio, et al.
0

The ML-Schema, proposed by the W3C Machine Learning Schema Community Group, is a top-level ontology that provides a set of classes, properties, and restrictions for representing and interchanging information on machine learning algorithms, datasets, and experiments. It can be easily extended and specialized and it is also mapped to other more domain-specific ontologies developed in the area of machine learning and data mining. In this paper we overview existing state-of-the-art machine learning interchange formats and present the first release of ML-Schema, a canonical format resulted of more than seven years of experience among different research institutions. We argue that exposing semantics of machine learning algorithms, models, and experiments through a canonical format may pave the way to better interpretability and to realistically achieve the full interoperability of experiments regardless of platform or adopted workflow solution.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/27/2011

Ontology Alignment at the Instance and Schema Level

We present PARIS, an approach for the automatic alignment of ontologies....
research
06/10/2021

IoT Virtualization with ML-based Information Extraction

For IoT to reach its full potential, the sharing and reuse of informatio...
research
07/24/2019

Semi Automatic Construction of ShEx and SHACL Schemas

We present a method for the construction of SHACL or ShEx constraints fo...
research
05/11/2023

CatE: Embedding 𝒜ℒ𝒞 ontologies using category-theoretical semantics

Machine learning with Semantic Web ontologies follows several strategies...
research
12/31/2022

Knowledge-Based Dataset for Training PE Malware Detection Models

Ontologies are a standard for semantic schemata in many knowledge-intens...
research
09/28/2021

Temporal Information and Event Markup Language: TIE-ML Markup Process and Schema Version 1.0

Temporal Information and Event Markup Language (TIE-ML) is a markup stra...
research
11/28/2019

Type Safety with JSON Subschema

JSON is a popular data format used pervasively in web APIs, cloud comput...

Please sign up or login with your details

Forgot password? Click here to reset