ANALYSIS OF MULTIDIMENSIONAL MEDICAL DATA USING PICTOGRAPHICS «CHERNOFF FACES»

The Many Faces of Multivariate Data: Chernoff Faces

Humans have the ability to discern subtle differences in facial expressions. What if multivariate data were represented in the form of a facial expression? Would it be easier to compare data sets? That is the argument behind Chernoff faces, an idea conceived by Herman Chernoff. Traditionally, Chernoff faces are a series of 2D shapes and lines that imitate facial features i.e. a triangle for a n...

analysis of ruin probability for insurance companies using markov chain

در این پایان نامه نشان داده ایم که چگونه می توان مدل ریسک بیمه ای اسپیرر اندرسون را به کمک زنجیره های مارکوف تعریف کرد. سپس به کمک روش های آنالیز ماتریسی احتمال برشکستگی ، میزان مازاد در هنگام برشکستگی و میزان کسری بودجه در زمان وقوع برشکستگی را محاسبه کرده ایم. هدف ما در این پایان نامه بسیار محاسباتی و کاربردی تر از روش های است که در گذشته برای محاسبه این احتمال ارائه شده است. در ابتدا ما نشا...

An Empirical Evaluation of Chernoff Faces, Star Glyphs, and Spatial Visualisations for Binary Data

Data visualization has the potential to assist humans in analyzing and comprehending large volumes of data, and to detect patterns, clusters and outliers that are not obvious using non-graphical forms of presentation. For this reason, data visualizations have an important role to play in a diverse range of applied problems, including data exploration and mining, information retrieval, and intel...

An Experimental Analysis of the Effectiveness of Features in Chernoff Faces

Chernoff faces have been proposed as a tool for scientific and information visualization. However, the effectiveness of this form of visualization is still open to speculation. Chernoff faces, it is suggested, make use of humans' apparently inherent ability to recognize faces and small changes in facial characteristics. Limited research has been conducted to assess how well Chernoff faces make ...

Big data analysis of public library operations and services by using the Chernoff face method