Anomaly detection in high dimensional data is becoming a fundamental research problem
that has various applications in the real world. However, many existing anomaly detection …

Abstract Machine learning (ML) models are nowadays used in complex applications in
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …

Massive simulations and arrays of sensing devices, in combination with increasing
computing resources, have generated large, complex, high-dimensional datasets used to …

Predictive analytics embraces an extensive range of techniques including statistical
modeling, machine learning, and data mining and is applied in business intelligence, public …

For high-dimensional data, this work proposes two novel visual exploration methods to gain
insights into the data aspect and the dimension aspect of the data. The first is a Dimension …

In this survey, 105 papers related to interactive clustering were reviewed according to seven
perspectives:(1) on what level is the interaction happening,(2) which interactive operations …

A scatter plot displays a relation between a pair of variables. Given a set of v variables, there
are v (v-1)/2 pairs of variables, and thus the same number of possible pair wise scatter plots …

In the age of big data, being able to make sense of data is an important key to success.
Interactive Visual Data Analysis advocates the synthesis of visualization, interaction, and …

Clustering technique plays a critical role in data mining, and has received great success to
solve application problems like community analysis, image retrieval, personalized …

Although deep neural networks have achieved state-of-the-art performance in several
artificial intelligence applications in the past decade, they are still hard to understand. In …