Visualizing Collation Results

Visualizing Clustering Results

Non-hierarchical clustering has a long history in numerical taxonomy [13] and machine learning [1] with many applications in fields such as data mining [2], statistical analysis [3] and information retrieval [17]. Clustering involves finding a specific number of subgroups (k) within a set of s observations (data points/objects); each described by d attributes. A clustering algorithm generates c...

Visualizing Regression Test Results

Visualizing Web Search Results

The explosive growth of the World Wide Web has offered more information and, concurrently, a need for improved navigation. In response to this problem, our aim for this project was to create a query result visualization paradigm that would provide a more co mprehensible presentation of returns and better support for result set exploration. In our particular interface, individual web pages are d...

Visualizing Search Results using SQWID

Most approaches to displaying search results create a list of results with some fixed order. Missing is the ability to explore common topics within the set of search results. This paper examines techniques to solve this problem and introduces SQWID, a system that uses many of these techniques. The SQWID (Search Query Weighted Information Display) system provides an interactive visualization of ...

Visualizing Random Forest’s Prediction Results

The current paper proposes a new visualization tool to help check the quality of the random forest predictions by plotting the proximity matrix as weighted networks. This new visualization technique will be compared with the traditional multidimensional scale plot. The present paper also introduces a new accuracy index (proportion of misplaced cases), and compares it to total accuracy, sensitiv...