منابع مشابه
Relational Data Learning
The past decade has witnessed many new theories and applications for statistical machine learning. However, most of statistical machine learning techniques are developed for a predetermined situation; it is static and inflexible, has flat structure and only deals with attributes (random variables) without any concept of objects. To some extent, these limitations make it hard to apply these stat...
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Transduction is an inference mechanism “from particular to particular”. Its application to classification tasks implies the use of both labeled (training) data and unlabeled (working) data to build a classifier whose main goal is that of classifying (only) unlabeled data as accurately as possible. Unlike the classical inductive setting, no general rule valid for all possible instances is genera...
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Feature engineering is one of the most important but tedious tasks in data science projects. This work studies automation of feature learning for relational data. We first theoretically proved that learning relevant features from relational data for a given predictive analytics problem is NP-hard. However, it is possible to empirically show that an efficient rule based approach predefining tran...
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Existing relational learning approaches usually work on complete relational data, but real-world data are often incomplete. This paper proposes the MGDA approach to learn structures of probabilistic relational model (PRM) from incomplete relational data. The missing values are filled in randomly at first, and a maximum likelihood tree (MLT) is generated from the complete data sample. Then, Gibb...
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I shall discuss new methods for solving the problem of generalizing from relational data. I consider a situation in which we have a set of concepts and a set of relations among these concepts, and the data consists of few instances of these relations that hold among the concepts; the aim is to infer other instances of these relations. My approach is to learn from the data a representation of th...
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ژورنال
عنوان ژورنال: Proceedings of the VLDB Endowment
سال: 2020
ISSN: 2150-8097
DOI: 10.14778/3415478.3415572