Add to ORKGAbstract. Instance Based Methods for classification are based on storing the complete training dataset. Once a query is received, it is compared with all the instances in the dataset, providing an answer as a function of the labels of the most similar instances. Opposite to this, Nearest Prototype Classification (NPC) obtains in training time a reduced set of prototypes that generalize the complete dataset, reducing time and memory constraints of the lazy approaches. This paper presents an algorithm for NPC with relational data. The method is based on a successful approach for NPC with propositional data, and on existing relational distance measures. Empirical results show the utility of the approach, both in classification accuracy and in ...
Rossi F, Hasenfuß A, Hammer B. Accelerating Relational Clustering Algorithms With Sparse Prototype R...
In this paper we consider the problem of learning nearest-prototype classifiers in any finite distan...
For many real-world applications it is important to choose the right representation language. While ...
Abstract. Relational instance-based learning (RIBL) algorithms offer high prediction capabilities. H...
Abstract—The nearest neighbor classifier is one of the most used and well-known techniques for perfo...
Abstract—The nearest neighbor (NN) rule is one of the most successfully used techniques to resolve c...
Prototype generation techniques have arisen as very competitive methods for enhancing the nearest ne...
this paper we will describe a relational instance-based algorithm which we terme
International audienceKnowledge graphs and other forms of relational data have become awidespread ki...
Instance based learning and clustering are popular methods in propositional machine learning. Both m...
ii Instance-based learning is a machine learning method that classifies new examples by comparing th...
based on nearest neighbor error minimization ∗ A prototype reduction algorithm is proposed which sim...
Perhaps the most straightforward classifier in the arsenal or machine learning techniques is the Nea...
An introduction is given to the use of prototype-based models in supervised machine learning. The ma...
The basic concepts of distance based classification are introduced in terms of clear-cut example sys...
Rossi F, Hasenfuß A, Hammer B. Accelerating Relational Clustering Algorithms With Sparse Prototype R...
In this paper we consider the problem of learning nearest-prototype classifiers in any finite distan...
For many real-world applications it is important to choose the right representation language. While ...
Abstract. Relational instance-based learning (RIBL) algorithms offer high prediction capabilities. H...
Abstract—The nearest neighbor classifier is one of the most used and well-known techniques for perfo...
Abstract—The nearest neighbor (NN) rule is one of the most successfully used techniques to resolve c...
Prototype generation techniques have arisen as very competitive methods for enhancing the nearest ne...
this paper we will describe a relational instance-based algorithm which we terme
International audienceKnowledge graphs and other forms of relational data have become awidespread ki...
Instance based learning and clustering are popular methods in propositional machine learning. Both m...
ii Instance-based learning is a machine learning method that classifies new examples by comparing th...
based on nearest neighbor error minimization ∗ A prototype reduction algorithm is proposed which sim...
Perhaps the most straightforward classifier in the arsenal or machine learning techniques is the Nea...
An introduction is given to the use of prototype-based models in supervised machine learning. The ma...
The basic concepts of distance based classification are introduced in terms of clear-cut example sys...
Rossi F, Hasenfuß A, Hammer B. Accelerating Relational Clustering Algorithms With Sparse Prototype R...
In this paper we consider the problem of learning nearest-prototype classifiers in any finite distan...
For many real-world applications it is important to choose the right representation language. While ...