Conflict Neutralization on Binary Space Partitioning

A Tutorial on Binary Space Partitioning Trees

A TS Fuzzy Model Derived from a Typical Multi-Layer Perceptron

In this paper, we introduce a Takagi-Sugeno (TS) fuzzy model which is derived from a typical Multi-Layer Perceptron Neural Network (MLP NN). At first, it is shown that the considered MLP NN can be interpreted as a variety of TS fuzzy model. It is discussed that the utilized Membership Function (MF) in such TS fuzzy model, despite its flexible structure, has some major restrictions. After modify...

Binary Space Partitioning as Intrinsic Reward

An autonomous agent embodied in a humanoid robot, in order to learn from the overwhelming flow of raw and noisy sensory, has to effectively reduce the high spatial-temporal data dimensionality. In this paper we propose a novel method of unsupervised feature extraction and selection with binary space partitioning, followed by a computation of information gain that is interpreted as intrinsic rew...

Binary Space Partitioning (BSP) Trees

A binary space partitioning (bsp) tree represents a recursive, hierarchical subdivision of d-dimensional space into convex subspaces. BSP trees provide a computational representation of space that provides both a search structure and a representation of geometry. Constructing a bsp tree consists of partitioning a subspace by means of a hyperplane, which intersects the interior of that subspace,...

Multi-class Classification: A Coding Based Space Partitioning

In this work we address the problem of multi-class classification in machine learning. In particular, we consider the coding approach which converts a multi-class problem to several binary classification problems by mapping the binary labeled space into several partitioned binary labeled spaces through binary channel codes. By modeling this learning problem as a communication channel, these cod...