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User Interface

Build Bayesian networks from data and/or expert opinion. Perform advanced queries and analytics.

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Bayesian networks

Fast & efficient software for Bayesian networks

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Decision graphs

Automate the decision making process. Also known as influence diagrams.

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Dynamic Bayesian networks

Model multi-variate time series and sequences

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Latent variables

Model hidden patterns / automate feature extraction

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Value of Information

Guide diagnostic / troubleshooting applications.

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Automated Insight

Automatically extract important information from data

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Log-Likelihood

How unusual/anomalous is your current data? Can your model be trusted?

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Fast inference

100x faster than a naive implementation. Over a decade of research.

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Data connectivity (API)

Connect to databases, spreadsheets, No-Sql stores and even custom data sources

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Missing data

Missing data natively supported during both learning and prediction, and for both discrete and continuous variables

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Discrete & continuous variables

Support for both discrete & continuous variable, as well as latent variables for expressing complex distributions

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Batch query

Perform queries on entire data sources

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Link strength / associations

How strong are the links/relationships in your model?

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Impact analysis

How susceptible are your predictions/queries to changes in evidence

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Data connectivity (User Interface)

Connect to many different databases, spreadsheets and No-Sql stores

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.NET API

A robust and efficient pure .NET API for building intelligent applications and services

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Java API

A robust and efficient pure Java API for building intelligent applications and services

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JavaScript API (coming soon)

A robust and efficient pure JavaScript API for building intelligent applications and services

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Cluster analysis

Automatically evaluate more expressive models and hidden patterns using cluster analysis for latent variables

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Case weights

Assign a weight to each row (or case). Great for historic data weighting, and learning from data with probabilities attached

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Sensitivity to parameters

How sensitive are you queries/predictions to the model parameters?

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Advanced query calculator

Perform advanced queries/prediction such as P(X,Y[t+3],Y[t+4] | Z)

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Noisy nodes

Model nodes with large numbers of parents

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Multi-variable nodes

Nodes can contain multiple variables, for powerful modeling

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Data (Scenario) explorer

Easily explore scenarios in the User Interface.

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Big data

Bayes Server supports Big Data platforms & technologies such as Apache Spark & Hadoop

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R integration

The Bayes Server API can be called from R. Our code center contains examples.

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Python integration

The Bayes Server API can be called from Python. Our code center contains examples.

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Matlab integration

The Bayes Server API can be called from Matlab. Our code center contains examples.

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Excel functions

The Bayes Server API can be called from within Excel functions. Our code center contains examples.

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Data sampling

Generate data from a model. Help understand/visualize your model, or generate test data.

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Parameter learning

Learn the parameters of your model from data. Includes support for missing data, discrete, continuous & hybrid networks

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Structural learning

Learn the structure (links) in a network. 4 different algorithms

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Online learning (adaptation)

Incrementally update (adapt) your model as new data arives.

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Discretization

Although continuous variables are fully supported, sometimes it can be useful to discretize. 3 discretization algorithms included.

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Add nodes from data

Advanced support for creating variables from a wide variety of data sources.

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Retract evidence

Predict a variable as if it did not have evidence set on it. Great for prediction and anomaly detection.

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Most probable explanation/sequence

Determine the most likely scenario (or sequence) given that you have an incomplete picture

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Comparison query

Compare scenarios

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Large networks

We have built networks with over 10000 variables

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Parameter tuning

Automatically adjust your model to achieve a desired goal.

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Soft/virtual evidence

Evidence can be uncertain on discrete variables

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Custom data sources (API)

The API is so flexible you can connect to custom/bespoke data sources

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Apache Spark

Bayes Server supports distributed processing on Apache Spark

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Confusion matrix

Evaluate the performance of your model

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Lift chart

Evaluate the performance of your model. Useful when the target is rare.

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Residual plot

Evaluate the performance of your model

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Conflict

Does you current data have conflicting evidence?

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Query explorer

Navigate large numbers of predictions/queries in the user interface

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Exact and approximate inference

4 different advanced inference algorithms

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Mutual information calculator

Multi-variate and conditional mutual information calculator (Discrete/continuous/hybrid).

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Feature importance

Determine the most influential features from data

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Entropy calculator

Multi-variate and conditional entropy calculator (Discrete/continuous/hybrid).

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Kullback-Leibler divergence calculator

Multi-variate Kullback-Leibler calculator. (Discrete or continuous)

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Arc reversal

Reverse the direction of links in your network, while maintaining the same overall network distribution

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Mesh query

Visualize predictions across 2 variables to easily identify patterns

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Relevance optimization

Our exact inference algorithms only touch what they need, increasing performance

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Tree width

Evaluate the complexity of your inference problem, given specific evidence and queries

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Evidence propagation

Our inference algorithms can auto propagate evidence through deterministic distributions, improving performance

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Disconnected networks

Networks can contain disconnected groups of nodes/variables

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