Constructing Interactive Visual Classification, Clustering and Dimension Reduction Models for n-D Data
Journal Title: Informatics - Year 2017, Vol 4, Issue 3
Abstract
The exploration of multidimensional datasets of all possible sizes and dimensions is a long-standing challenge in knowledge discovery, machine learning, and visualization. While multiple efficient visualization methods for n-D data analysis exist, the loss of information, occlusion, and clutter continue to be a challenge. This paper proposes and explores a new interactive method for visual discovery of n-D relations for supervised learning. The method includes automatic, interactive, and combined algorithms for discovering linear relations, dimension reduction, and generalization for non-linear relations. This method is a special category of reversible General Line Coordinates (GLC). It produces graphs in 2-D that represent n-D points losslessly, i.e., allowing the restoration of n-D data from the graphs. The projections of graphs are used for classification. The method is illustrated by solving machine-learning classification and dimension-reduction tasks from the domains of image processing, computer-aided medical diagnostics, and finance. Experiments conducted on several datasets show that this visual interactive method can compete in accuracy with analytical machine learning algorithms.
Authors and Affiliations
Boris Kovalerchuk and Dmytro Dovhalets
Keywords
Related Articles
- EP ID EP44094
- DOI https://doi.org/10.3390/informatics4030023
- Views 238
- Downloads 0
An Empirical Study on Importance of Modeling Parameters and Trading Volume-Based Features in Daily Stock Trading Using Neural Networks
There have been many machine learning-based studies to forecast stock price trends. These studies attempted to extract input features mostly from the price information with little focus on the trading volume informatio...
Artery Segmentation in Ultrasound Images Based on an Evolutionary Scheme
Segmentation in ultrasound (US) images is a challenge in computer vision, due to the high signal noise, artifacts that produce discontinuities in the boundaries and shadows that hide part of the received signal. In thi...
Back-Off Time Calculation Algorithms in WSN
In a Mobile Wireless Sensor Mesh Network (MWSMN), based on the IEEE 802.15.4 standard, low power consumption is vitally important since the network devices are mostly battery driven. This is especially true for devices...
Improvement in the Efficiency of a Distributed Multi-Label Text Classification Algorithm Using Infrastructure and Task-Related Data
Distributed computing technologies allow a wide variety of tasks that use large amounts of data to be solved. Various paradigms and technologies are already widely used, but many of them are lacking when it comes to th...
Applications of Blockchain Technology to Logistics Management in Integrated Casinos and Entertainment
The gaming industry has evolved into a multi-functional smart city that combines integrated casinos and entertainment (ICE). ICE logistics involve supply chains with various stages in geographically-distributed locatio...