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Differences between the BayesiaLab's Standard and Professional versions
| Features | Standard Edition | Professional Edition |
|---|---|---|
| Inference | ||
| Exact Inference with Junction Tree | X | X |
| Approximate Inference with Importance Sampling | X | X |
| Interactive inference based on Evidence Scenario file or on the current database | X | X |
| Interactive Bayesian updating based on Evidence Scenario file or on the current database | X | X |
| Adaptive Questionnaire with respect to a target variable/target state | X | X |
| Adaptive Questionnaire with respect to a target modality | X | X |
| Batch Labeling of the target variable | - | X |
| Batch Inference of the Not Observable variables | - | X |
| Batch Labeling of the target variable with the Most Probable Explanation (MPE) | - | X |
| Batch Inference of the Not Observable variables with the MPE | - | X |
| Batch Joint Probability | - | X |
| Batch Likelihood | - | X |
| Markov Blanket exportation | ||
| SAS Macro | - | Available on subscription only |
| JavaScript | - | Available on subscription only |
| PHP | - | Available on subscription only |
| Data | ||
| Data generation with MCMC | - | X |
| JDBC/ODBC connection | - | X |
| Database saving | - | X |
| Missing Value Imputation | - | X |
| Weights | X | X |
| Stratification | - | X |
| Data Type (learning/test) | X | X |
| Import/Export Dictionaries | - | X |
| Discretization of continuous variables | ||
| Manual based on the repartition function | X | X |
| Equal distances | X | X |
| Equal frequencies | X | X |
| K-Means | X | X |
| Decision tree | - | X |
| Aggregation of discrete modalities | ||
| Manual | X | X |
| Manual based on the correlation with a target variable | X | X |
| Semi-Automatic wrt the correlation with a target state | X | X |
| Decision tree based on the correlation with a target state | - | X |
| Missing values processing | ||
| Filtering | X | X |
| Replacement | X | X |
| Inference | X | X |
| Association discovery | ||
| Maximum Weight Spanning Tree | X | X |
| EQ | - | X |
| SopLEQ | - | X |
| Taboo Search | X | X |
| Taboo Order | - | X |
| Target node Characterization | ||
| Naïve | X | X |
| Augmented Naïve | X | X |
| Tree Augmented Naïve | X | X |
| Sons & Spouses | - | X |
| Markov Blanket | - | X |
| Augmented Markov Blanket | - | X |
| Minimal Augmented Markov Blanket | - | X |
| Semi-Supervised Learning | - | X |
| Clustering | ||
| Variable clustering | - | X |
| Data clustering (EM / KMeans) | - | X |
| Multiple clustering | - | X |
| Targeted Evaluation | ||
| Multiple thresholds | - | X |
| Global Precision | X | X |
| Pearson Correlation Coefficient (R and R2) | X | X |
| Confusion Matrix | X | X |
| Lift chart | - | X |
| Gain chart | - | X |
| ROC curve | - | X |
| Global Evaluation | ||
| Log-Likelihood | X | X |
| Contingency Table Fit | X | X |
| Extract Database wrt Likelihoods | - | X |
| Automatic layout algorithms | ||
| Symmetric | X | X |
| Dynamic | X | X |
| Genetic | - | X |
| Mutual Information | - | X |
| Random | X | X |
| Graphical Network analysis | ||
| Arc Force | X | X |
| Pearson’s Correlation | X | X |
| Node Force | X | X |
| Correlation with the Target node/state | X | X |
| Correlation with the Target state | X | X |
| Influence paths | X | X |
| Causal analysis (essential graphs) | X | X |
| Target modality Optimization | X | X |
| Target node Sensitivity analysis | X | X |
| Parameters Sensitivity analysis | X | X |
| Most Probable Explanation | X | X |
| Neighborhood analysis | X | X |
| Mosaic analysis | X | X |
| Influence Analysis wrt Target Node | X | X |
| Target Mean Analysis | X | X |
| HTML Analysis Report | ||
| Network | X | X |
| Relationships analysis | X | X |
| Correlations with the Target Node | X | X |
| Target Dynamic Profile | X | X |
| Total Effects on Target | X | X |
| Evidences analysis | X | X |
| Tools | ||
| Network comparisons | X | X |
| Cross-Validation (Supervised/Unsupervised) | - | X |
| Multi-Quadrant Analysis | - | X |
| Special nodes | ||
| Hidden | X | X |
| Decision | X | X |
| Utility | X | X |
| Constraint | X | X |
| Dynamic Bayesian networks | ||
| Dynamic Bayesian networks | X | X |
| Action policy learning | ||
| Static Bayesian networks | X | X |
| Dynamic Bayesian networks | X | X |
| Graphics | ||
| Histogram | X | X |
| Repartition function | X | X |
| Occurrence matrix with Khi2 test | X | X |
| 2D Scatter points | - | X |
| 3D Scatter points | - | X |
| Bubble chart | - | X |
| Multilingual | ||
| English | X | X |
| French | X | X |
| Spanish | X | X |
| Chineese | X | X |
| Japanese | X | X |
| Cross-Platform (Java technology) | ||
| Cross-Platform (Java technology) | X | X |