Results
author = "Bratko, Ivan"
Learning Qualitative Models
Description :
In general, modeling is a complex and creative task, and building qualitative models is no exception. One way of automating this task is by means of machine learning. Observed behaviors of a modeled system are used as examples for a learning algorithm that constructs a model that is consistent with ...
Repository :
AI Magazine
Language(s) :
English
Improving numerical prediction with qualitative constraints
Description :
The usual numerical learning methods, that are primarily concerned with finding a good numerical fit to the data, often make predictions that do not correspond to the qualitative mechanisms in the domain of modelling or a domain expert's intuition. Consistency of numerical predictions with a given q...
Repository :
ePrints.FRI - Fakulteta za računalništvo in informatiko, Univerza v Ljubljani
Language(s) :
Undetermined
Testing the Significance of Attribute Interactions
Description :
Attribute interactions are the irreducible dependencies between attributes. Interactions underlie feature relevance and selection, the structure of joint probability and classification models: if and only if the attributes interact, they should be connected. While the issue of 2-way interactions, es...
Repository :
ePrints.FRI - Fakulteta za računalništvo in informatiko, Univerza v Ljubljani
Language(s) :
Undetermined
Analyzing Attribute Dependencies
Description :
Many effective and efficient learning algorithms assume independence of attributes. They often perform well even in domains where this assumption is not really true. However, they may fail badly when the degree of attribute dependencies becomes critical. In this paper, we examine methods for detecti...
Repository :
ePrints.FRI - Fakulteta za računalništvo in informatiko, Univerza v Ljubljani
Language(s) :
Undetermined
Combining Learning Constraints and Numerical Regression
Description :
Usual numerical learning methods are primarily concerned with finding a good numerical fit to data and often make predictions that do not correspond to qualitative laws in the domain of modelling or expert intuition. In contrast, the idea of $Q^2$ learning is to induce qualitative constraints from t...
Repository :
ePrints.FRI - Fakulteta za računalništvo in informatiko, Univerza v Ljubljani
Language(s) :
Undetermined
Quantifying and Visualizing Attribute Interactions: An Approach Based on Entropy
Description :
Interactions are patterns between several attributes in data that cannot
be inferred from any subset of these attributes. While mutual information
is a well-established approach to evaluating the interactions between two
attributes, we surveyed its generalizations as to quantify interactions
between...
Repository :
ePrints.FRI - Fakulteta za računalništvo in informatiko, Univerza v Ljubljani
Language(s) :
Undetermined
Analyzing Attribute Dependencies
Description :
Many effective and efficient learning algorithms assume independence of attributes. They often perform well even in domains where this assumption is not really true. However, they may fail badly when the degree of attribute dependencies becomes critical. In this paper, we examine methods for detecti...
Repository :
ePrints.FRI - Fakulteta za računalništvo in informatiko, Univerza v Ljubljani
Language(s) :
Undetermined
Quantifying and Visualizing Attribute Interactions
Description :
Interactions are patterns between several attributes in data that cannot be
inferred from any subset of these attributes. While mutual information is a
well-established approach to evaluating the interactions between two
attributes, we surveyed its generalizations as to quantify interactions betwe...
Repository :
arXiv
Language(s) :
Undetermined
Kikuchi-Bayes: Factorized Models for Approximate Classification in Closed Form
Description :
We propose a simple family of classification models, based on the Kikuchi approximation to free energy. We note that the resulting product of potentials is not normalized, but for classification it is easy to perform the normalization for each instance separately. We propose a learning method based ...
Repository :
ePrints.FRI - Fakulteta za računalništvo in informatiko, Univerza v Ljubljani
Language(s) :
Undetermined
Learning to Fly Simple and Robust
Description :
We report on new experiments with machine learning in the reconstruction of human sub-cognitive skill. The particular problem considered is to generate a clone of a human pilot performing a flying task on a simulated aircraft. The work presented here uses the human behaviour to create constraints fo...
Repository :
ePrints.FRI - Fakulteta za računalništvo in informatiko, Univerza v Ljubljani
Language(s) :
Undetermined