Add to ORKGLazy learning is a memory-based technique that, once a query is received, extracts a prediction interpolating locally the neighboring examples of the query which are considered relevant according to a distance measure. This toolbox implements a data-driven method to select on a query-by-query basis the optimal number of neighbors to be considered for each prediction. As an efficient way to identify and validate local models, the recursive least squares algorithm is adopted. Furthermore, beside the winner-takes-all strategy for model selection, the toolbox implements also a local combination, performed on a query-by-query basis, of the most promising models. This manual describes the functions included in the toolbox as well as the algorithm...
Learning in the context of constraint solving is a technique by which previously unknown constraints...
Classification is a machine learning technique whose objective is the prediction of the class member...
An approach is presented to learning high dimensional functions in the case where the learning algor...
Lazy learning is a memory-based technique that, once a query is received, extracts a prediction inte...
Lazy learning is a memory-based technique that, once a query is received, extracts a prediction inte...
Lazy learning is a memory-based technique that, once a query is received, extracts a prediction inte...
Lazy Learning is a memory-based technique that, once a query is received, extracts a prediction inte...
In this paper, we identify a similar linear model in a local way, using a lazy learning algorithm. T...
In this paper, we propose a lazy learning strategy for building classification learning models. Inst...
The traditional approach to supervised learning is global modeling which describes the relationship ...
Local learning techniques, for each query, extract a predic-tion interpolating locally the neighbori...
Linear and nonlinear regression problems are very common in different fields of science and engineer...
Lazy local learning methods train a classifier “on the fly ” at test time, using only a subset of th...
Lazy learning methods have been used to deal with problems in which the learning examples are not ev...
Learning in the context of constraint solving is a technique by which previously unknown constraints...
Learning in the context of constraint solving is a technique by which previously unknown constraints...
Classification is a machine learning technique whose objective is the prediction of the class member...
An approach is presented to learning high dimensional functions in the case where the learning algor...
Lazy learning is a memory-based technique that, once a query is received, extracts a prediction inte...
Lazy learning is a memory-based technique that, once a query is received, extracts a prediction inte...
Lazy learning is a memory-based technique that, once a query is received, extracts a prediction inte...
Lazy Learning is a memory-based technique that, once a query is received, extracts a prediction inte...
In this paper, we identify a similar linear model in a local way, using a lazy learning algorithm. T...
In this paper, we propose a lazy learning strategy for building classification learning models. Inst...
The traditional approach to supervised learning is global modeling which describes the relationship ...
Local learning techniques, for each query, extract a predic-tion interpolating locally the neighbori...
Linear and nonlinear regression problems are very common in different fields of science and engineer...
Lazy local learning methods train a classifier “on the fly ” at test time, using only a subset of th...
Lazy learning methods have been used to deal with problems in which the learning examples are not ev...
Learning in the context of constraint solving is a technique by which previously unknown constraints...
Learning in the context of constraint solving is a technique by which previously unknown constraints...
Classification is a machine learning technique whose objective is the prediction of the class member...
An approach is presented to learning high dimensional functions in the case where the learning algor...