Introduction | Data Preparation | Crisp (Boolean) Predicates Example | Fuzzy Predicates Example | Advanced Data Preparation Capabilities | Pre-defined Patterns | Search for Association Rules | Conditional Correlations | Contrast Patterns | Baseline Contrasts | Complement Contrasts | Paired Baseline Contrasts | Post-processing and Visualization | Visualizing Association Rules with Diamond Plots | Interactive Exploration | Advanced Use | Custom Patterns with dig() | Grid-Based Patterns with dig_grid() | Summary | Next Steps

Introduction | Common Rule Parameters | Pre-defined Rule Types | rRule() | markdownRule() | knitrRule() | copyRule() | depRule() | subdirRule() | offlineRule() | Custom Rules | Using inShell() | Summary | See Also

Introduction | Key Features | Why Use rmake? | Installation | Prerequisites | System Requirements | Environment Variables | When is R_HOME needed? | Finding R_HOME | Setting R_HOME | Project Initialization | Creating Skeleton Files | Basic Example | Step 1: Create the Data File | Step 2: Create the Processing Script | Step 3: Define the Build Rule | Step 4: Run the Build | Using the Pipe Operator | Adding a Markdown Report | Running Make | From R | From Command Line | From RStudio | Visualizing Dependencies | Multiple Dependencies | Rule Types | Next Steps | Summary | Resources

Introduction | Project Initialization | Running the Build Process | Cleaning Up | Parallel Execution | Summary | See Also

Introduction | Tasks | Executing Tasks | Assigning Rules to Tasks | Use Cases for Tasks | Parameterized Execution | Accessing Parameters in Scripts | Using getParam() | Built-in Parameters | Rule Templates | Simple Template | Template with Multiple Variables | Combining Templates with Parameters | Template Variables in Parameters | Common Pitfall: Multiple Rules for Same Target | Combining Tasks and Templates | Best Practices | For Tasks | For Templates | Summary

Introduction | Data Preparation with partition() | Preparation of Crisp (Boolean) Predicates | Data-Driven Breakpoint Selection with .style | Preparation of Triangular and Raised-Cosine Fuzzy Predicates | Preparation of Trapezoidal Fuzzy Predicates | Identifying and Removing Uninformative Columns | Testing for Almost Constant Columns | Removing Almost Constant Columns | Finding Tautologies in Data | What are Tautologies? | Using dig_tautologies() | Parameters | Using Tautologies to Filter Searches | Summary

Introduction | Fuzzy logic and fuzzy sets | Compositions of fuzzy relations | Evaluative linguistic expressions | Fuzzy association rules | Perception-based Logical Deduction | Applicability | Conclusion

Introduction | Hasse Diagrams | Visualization of All-Pairwise Comparison Tests | Notes on Partial Orderness of Multiple Comparisons | Direct Hasse Diagram Plot | Conclusion