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1. Following comprehensive testing and research, CXAIR now provides extensive statistical
analysis and modelling capability using Bayesian predictive analytics functionality.
This enables users to identify cohorts of data and create models over wide data sets to
understand relationships between data items and key factors that affect or contribute to
outcomes of interest.
Within CXAIR, users are able to take existing data and create a filtered dataset. This is then
used to build Bayesian network models based on different configurable learning
algorithms.
Bayesian Networks
Features
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2. Features
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These models can be viewed visually, highlighting relationships in the data and probabilities
of outcomes based on selected variables.
Models can be used to identify cohorts of individuals or related segments of data then be
saved and applied to specific data subsets as new data is loaded into the system. This allows
the origin of possible outcomes to be stored alongside the real and unknown outcomes.
The augmented data can then be validated for accuracy before being presented to users
for real-time risk stratification, reporting and statistical analysis.
After a model has been created, the visualisation options in CXAIR can be used to highlight
and view key data in a format more appropriate for distribution to business users, with a
wealth of views and visualisations available to ensure the user experience with the model is
as interactive as possible.
CXAIR has extensive charting capability including in-built features such as SPC charting,
Mean, Median, Standard Deviation, Banding and Ranking algorithms while also having over
100 chart types ranging from standard bar and column to funnel plots, Venn diagrams,
bullet charts, radial charts, histograms, box and whisker plots, scatter plots, spider charts,
time series and more. All charts have trend functionality and customisable totals and
calculations.
For further information or for a demonstration, please contact info@connexica.com
Bayesian Networks