Searching for authors named "Nicolas Lachiche" – sorted by Relevance.
23 documents found, showing 1 through 10.
Next 10 →
-
Induction Descriptive: Un Nouveau Modèle Pour La Découverte De Connaissances
- …Most research in Inductive Logic Programming has been concerned with a form of induction called explanatory induction. Another form of induction, called descriptive induction, is presented in this article. This kind of induction is appropriate to discovery of regularities in databases and is therefo…
- Add To MetaCart
-
Abduction and Induction From a Non-Monotonic Reasoning Perspective
- …. In this chapter, induction and abduction are investigated in a nonmonotonic reasoning framework. We recall that several meanings can be given to logic-based abduction and induction. In particular, we distinguish explanatory and descriptive induction. Explanatory induction is closely related to abd…
- Cited by 5 (0 self) – Add To MetaCart
-
Rule-Based Classification without Rules thanks to Instance-Based Learning
- …A new approach to learning from examples, called scope classification, is introduced. Close to Instance-Based Learning, scope classification is at the core of rule-based classification.…
- Add To MetaCart
-
A Model for Generalization based on Confirmatory Induction
- …Confirmatory induction is based on the assumption that unknown individuals are similar to known ones, i.e. they satisfy the properties shared by known individuals. This assumption can be represented inside a non-monotonic logical framework. Accordingly, existing approaches to confirmatory induction …
- Cited by 2 (1 self) – Add To MetaCart
-
Abduction, Induction and Completion Policies
- …. In this paper, we are mainly concerned with abduction and confirmatory induction. While both reasoning models can be related to deduction w.r.t. a completed knowledge base, we claim that they do not basically rely on the same completion policies. Intuitively, induction requires individuals of the…
- Cited by 2 (1 self) – Add To MetaCart
-
A First-Order Approach to Unsupervised Learning
- …. This paper deals with learning first-order logic rules from data lacking an explicit classification predicate. Consequently, the learned rules are not restricted to predicate definitions as in supervised Inductive Logic Programming. First-order logic offers the ability to deal with structured, mul…
- Cited by 3 (2 self) – Add To MetaCart
-
1BC: a First-Order Bayesian Classifier
- …. In this paper we present 1BC, a first-order Bayesian Classifier. Our approach is to view individuals as structured terms, and to distinguish between structural predicates referring to subterms (e.g. atoms from molecules), and properties applying to one or several of these subterms (e.g. a bond bet…
- Cited by 37 (18 self) – Add To MetaCart
-
Improving Accuracy and Cost of Two-Class and Multi-Class Probabilistic Classifiers Using ROC Curves
- …The probability estimates of a naive Bayes classifier are inaccurate if some of its underlying independence assumptions are violated. The decision criterion for using these estimates for classification therefore has to be learned from the data. This…
- Cited by 22 (2 self) – Add To MetaCart
-
Good and Bad Practices in Propositionalisation
- …Data is mainly available in relational formats, so relational data mining receives a lot of interest. Propositionalisation consists in changing the representation of relational data in order to apply usual attribute-value learning systems. Data mining practitioners are not necessarily aware of e…
- Add To MetaCart
-
A first-order representation for knowledge discovery and Bayesian classification on relational data
- …In this paper we consider different representations for relational learning problems, with the aim of making ILP methods more applicable to real-world problems. In the past, ILP tended to concentrate on the term representation, with the flattened Datalog representation as a `poor man's version'. …
- Add To MetaCart
Showing 1 through 10.
Next 10 →
