HOTTBOX: Higher Order Tensor ToolBOX

TL;DR

HOTTBOX is a comprehensive Python library that facilitates scalable analysis, visualization, and decomposition of multi-dimensional tensor data, integrating advanced algorithms like tensor classification and data fusion for multidisciplinary applications.

Contribution

It introduces a unified API for tensor operations, scalable algorithms for tensor classification and data fusion, and emphasizes interactive visualization for big data analysis.

Findings

Provides efficient tensor decomposition methods

Supports advanced multi-linear classification algorithms

Enables integration with other data science tools

Abstract

HOTTBOX is a Python library for exploratory analysis and visualisation of multi-dimensional arrays of data, also known as tensors. The library includes methods ranging from standard multi-way operations and data manipulation through to multi-linear algebra based tensor decompositions. HOTTBOX also comprises sophisticated algorithms for generalised multi-linear classification and data fusion, such as Support Tensor Machine (STM) and Tensor Ensemble Learning (TEL). For user convenience, HOTTBOX offers a unifying API which establishes a self-sufficient ecosystem for various forms of efficient representation of multi-way data and the corresponding decomposition and association algorithms. Particular emphasis is placed on scalability and interactive visualisation, to support multidisciplinary data analysis communities working on big data and tensors. HOTTBOX also provides means for integration with other popular data science libraries for visualisation and data manipulation. The source code, examples and documentation ca be found at https://github.com/hottbox/hottbox.