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VisuMap
Version 3.0
VisuMap
helps people to understand high-dimensional, complex, large or
otherwise 'difficult' datasets. It enables researchers, analysts and
other professionals to grasp trends and patterns by interacting with 2D and 3D maps of their data.
By
integrating the latest mathematical techniques for presenting multiple
dimensions of data in relation to eath other, VisuMap enables users to
apply the power of their visual perception and intuition.
This
harnessing of human perceptual power, together with unprecedented ease
of use, means that VisuMap has succeeded where conventional data mining
tools have failed. At the same time, developers and system
administrators will find extensive scripting and plug-in interfaces
that encourage them to customize, integrate anhd extend VisuMap to suit
their end-users' needs.
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Multidimesnional Scaling (data mapping):
- Relational Perspective Map (RPM)
- Multidimensional Scaling (Sammon Map)
- Curvilinear Component Analysis (CCA)
- Principal Component Analysis (PCA)
- MDS by SMACOF Algorithm
- Correspondence Analysis
- Stochastic Neighbor Embedding (t-SNE)
- Kernel PCA
Data Clustering:
- Self-Organizing Map (Kohonen Net)
- K-Mean Clustering
- Metric Sampling
- Agglomerative Clustering
- Affinity Propagation
- Self-Organzing Graph
Data Visualization & Exploration:
- 13 built-in metrics: euclidean, mahalanobis, pearson
correlation, speaman ranking, wedge- hedge, etc.
- Dynamically linked data views: bar, curve, spectrum,
table, tree, Shepard diagram, atlas, dashboard, etc..
- Attribute map analysis
- Hardware accelerated 3D animation
Programming Interfaces:
- Scripting interface for automation
- DotNet plug-in interface for extension
- Import/Export formats: ASCII, SQL-DB,
JPEG, GIF, SVG etc.(10 image formats).
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Applications
- Pharmaceutics
- Bioinformatics
- Financial analysis
- Market analysis
- Telecommunication industry
- Internet traffic analysis
- Quality control
System Requirements
More Information
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