Software
From: Jouffe Lionel
Date: 20 Mar 2008
Subject: Release of BayesiaLab 4.4, the leading Bayesian Network software for Data Mining
Bayesia announces the release of
BayesiaLab 4.4, the software for efficient Data Mining with Bayesian
Networks (academic licenses available from 140 Euros).
Here are some new features of this release:
- Mosaic Analysis: powerful analysis tool
allowing to get a graphical representation of the joint probability
distribution of a subset of variables. By using the standardized
Pearson residuals, these graphs can also be used to accurately analyze
the statistical significance of the probabilistic relations between the
variable states. The "Horizontal Diagram" version is particularly
useful to analyze clustering results;
- Dynamic Profile: new analysis report
that uses an incremental optimization procedure to optimize the selected criterion (State
Probability, Variable Mean or Probability Difference between two States).
By taking into account the probabilistic relations between the profile
variables, this analysis is particularly fitted to searching the
best levers;
- Tree Augmented Naive Bayes: partially
predefined structure allowing to relax the strong hypothesis of
conditional independence that holds in the Na�ve architecture where,
knowing the target node value, each node becomes independent of the
other nodes. This architecture is based on the Na�ve architecture on
which a maximum spanning tree is learned. The prediction accuracy is
better than the one obtained by the Na�ve
architecture, and this algorithm is much quicker than the Augmented
Na�ve algorithm;
- Data Clustering: the clustering algorithm can now be tuned by using
the Settings: the Drift measures
the difference between the theoretical (during learning) and the true
(after the imputation on the learning set) probability distributions of
the clusters. The Purity is the mean of the data assignment probability
in the clusters. Increasing these parameters increases the constraints
and reduces the number of obtained clusters;
- and, as usual,
increased ergonomics of the interface and performance improvements.
You can consult the
newsletter
that describes more in details the 80 new functionalities of
BayesiaLab 4.4,
download BayesiaLab 4.4
for a new 30 days evaluation period, and you can also have a look at the
dynamic
and
static presentations
that illustrate successful applications of BayesiaLab.
| |
|