Add to ORKGThis thesis is specialized in instance based learning algorithms. Main goal is to create an application for educational purposes. There are instance based learning algorithms (IBL), nearest neighbor algorithms and kd-trees described theoretically in this thesis. Practical part is about making of tutorial application. Application can generate data, classified them with nearest neighbor algorithm and is able of IB1, IB2 and IB3 algorithm testing
This paper presents a novel instance-based learning methodology the Binomial-Neighbour (B-N) algorit...
AbstractThis paper presents average-case analyses of instance-based learning algorithms. The algorit...
This paper focuses on the creation and presentation of a user-friendly experience for developing com...
Instance Based Learning (IBL) results in classifying a new instance by examining and comparing it to...
The presented thesis focuses on instance-based learning (IBL) methods. The groundwork of instance-ba...
ii Instance-based learning is a machine learning method that classifies new examples by comparing th...
Instance-based learning is a machine learning method that classifies new examples by comparing them ...
This dissertation introduces a framework for specifying instance-based algorithms that can solve sup...
This paper presents PAC-learning analyses for instance-based learning algorithms for both symbolic a...
this paper we will describe a relational instance-based algorithm which we terme
The thesis focuses on instance-based learning methods. It is concerned with two particular prototype...
Storing and using specific instances improves the performance of several supervised learning algorit...
The basic nearest-neighbor rule generalizes well in many domains but has several shortcomings, inclu...
We describe a new instance-based learning algorithm called the Boundary Forest (BF) algorithm, that ...
Abstract. This paper introduces a learning system iBARET (Instance-BAsed REasoning Tool). This syste...
This paper presents a novel instance-based learning methodology the Binomial-Neighbour (B-N) algorit...
AbstractThis paper presents average-case analyses of instance-based learning algorithms. The algorit...
This paper focuses on the creation and presentation of a user-friendly experience for developing com...
Instance Based Learning (IBL) results in classifying a new instance by examining and comparing it to...
The presented thesis focuses on instance-based learning (IBL) methods. The groundwork of instance-ba...
ii Instance-based learning is a machine learning method that classifies new examples by comparing th...
Instance-based learning is a machine learning method that classifies new examples by comparing them ...
This dissertation introduces a framework for specifying instance-based algorithms that can solve sup...
This paper presents PAC-learning analyses for instance-based learning algorithms for both symbolic a...
this paper we will describe a relational instance-based algorithm which we terme
The thesis focuses on instance-based learning methods. It is concerned with two particular prototype...
Storing and using specific instances improves the performance of several supervised learning algorit...
The basic nearest-neighbor rule generalizes well in many domains but has several shortcomings, inclu...
We describe a new instance-based learning algorithm called the Boundary Forest (BF) algorithm, that ...
Abstract. This paper introduces a learning system iBARET (Instance-BAsed REasoning Tool). This syste...
This paper presents a novel instance-based learning methodology the Binomial-Neighbour (B-N) algorit...
AbstractThis paper presents average-case analyses of instance-based learning algorithms. The algorit...
This paper focuses on the creation and presentation of a user-friendly experience for developing com...