PROJECT TITLE :

InterAxis: Steering Scatterplot Axes via Observation-Level Interaction

ABSTRACT:

Scatterplots are effective visualization techniques for multidimensional information that use two (or 3) axes to visualize information things as a point at its corresponding x and y Cartesian coordinates. Typically, each axis is bound to one data attribute. Interactive exploration happens by changing the info attributes certain to each of these axes. Within the case of using scatterplots to visualize the outputs of dimension reduction techniques, the x and y axes are mixtures of the true, high-dimensional information. For these spatializations, the axes present usability challenges in terms of interpretability and interactivity. That is, understanding the axes and interacting with them to create changes will be difficult. During this paper, we have a tendency to gift InterAxis, a visible analytics technique to properly interpret, define, and modification an axis in a very user-driven manner. Users are given the flexibility to define and modify axes by dragging information things to either side of the x or y axes. from that the system computes a linear combination of data attributes and binds it to the axis. Any, users will directly tune the positive and negative contribution to those advanced axes by using the visualization of data attributes that correspond to every axis. We have a tendency to describe the details of our technique and demonstrate the supposed usage through two eventualities.