|
Genna Overview |
Genna Uniqueness |
Genna Key features |
Genna Userbase |
Genna System Requirements
Genna
Summary
GENNA is a hybrid data mining algorithm that couples
the strengths of the Nearest Neighbour and Genetic
data mining algorithms to provide accurate models
implicit within the data set provided to it for
learning. Typically, the Nearest Neighbour algorithm
is dependent on the modelling expert to optimise
various parameters that can affect the performance
of the model. GENNA uniquely uses the Genetic Algorithm
to automatically optimise these parameters making
the algorithm easy to use. Additionally GENNA uses
innovative indexing mechanisms to speed up the prediction
process which has traditionally been a bottleneck
with Nearest Neighbour algorithms.
GENNA can be used for classification and regression,
predictive tasks. The perspicuity of the model and
cognitive basis makes it particularly suited to
applications where justification of individual predictions
are key. Examples of such domains are government
and medicine.
Typical example applications to which GENNA has
been applied include:
• Churn Analysis
• House Price Prediction for Mass Appraisal
• Prognosis of Colorectal Patients
back to products |
|
|
|
Coral
Summary
