Semantic Web Stack

Data visualization

Pure mathematics

Learning analytics

Mathematics

Cultural analytics

Computer graphics

Human–computer interaction

Engineering

Semantic analytics

Artificial intelligence

Systems engineering

Semantic Web

Set (abstract data type)

Programming language

Data science

Visualization

Computer science

Task (project management)

Visual analytics

Field (mathematics)

Analytics

Interactive visual analysis

Computational Visual Media

Visual analytics for machine learning has recently evolved as one of the most exciting areas in the field of visualization. To better identify which research topics are promising and to learn how to apply relevant techniques in visual analytics, we systematically review 259 papers published in the last ten years together with representative works before 2010. We build a taxonomy, which includes three first-level categories: techniques before model building, techniques during modeling building, and techniques after model building. Each category is further characterized by representative analysis tasks, and each task is exemplified by a set of recent influential works. We also discuss and highlight research challenges and promising potential future research opportunities useful for visual analytics researchers.

A survey of visual analytics techniques for machine learning