Package: CaseBasedReasoning 0.3
CaseBasedReasoning: Case Based Reasoning
Case-based reasoning is a problem-solving methodology that involves solving a new problem by referring to the solution of a similar problem in a large set of previously solved problems. The key aspect of Case Based Reasoning is to determine the problem that "most closely" matches the new problem at hand. This is achieved by defining a family of distance functions and using these distance functions as parameters for local averaging regression estimates of the final result. The optimal distance function is chosen based on a specific error measure used in regression estimation. This approach allows for efficient problem-solving by leveraging past experiences and adapting solutions from similar cases. The underlying concept is inspired by the work of Dippon J. et al. (2002) <doi:10.1016/S0167-9473(02)00058-0>.
Authors:
CaseBasedReasoning_0.3.tar.gz
CaseBasedReasoning_0.3.zip(r-4.5)CaseBasedReasoning_0.3.zip(r-4.4)
CaseBasedReasoning_0.3.tgz(r-4.4-x86_64)CaseBasedReasoning_0.3.tgz(r-4.4-arm64)
CaseBasedReasoning_0.3.tar.gz(r-4.5-noble)CaseBasedReasoning_0.3.tar.gz(r-4.4-noble)
CaseBasedReasoning.pdf |CaseBasedReasoning.html✨
CaseBasedReasoning/json (API)
NEWS
| # Install 'CaseBasedReasoning' in R: |
| install.packages('CaseBasedReasoning', repos = c('https://sipemu.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/sipemu/case-based-reasoning/issues
Last updated 6 months agofrom:4a8d128fe5. Checks:ERROR: 1 WARNING: 5. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | FAIL | Nov 14 2024 |
| R-4.5-win-x86_64 | WARNING | Nov 14 2024 |
| R-4.5-linux-x86_64 | WARNING | Nov 14 2024 |
| R-4.4-win-x86_64 | WARNING | Nov 14 2024 |
| R-4.4-mac-x86_64 | WARNING | Nov 14 2024 |
| R-4.4-mac-aarch64 | WARNING | Nov 14 2024 |
Exports:asDistObjectCoxModeldepth_distancedistanceRandomForestedges_between_terminal_nodesgenerate_gridLinearModelLogisticModelproximity_distanceranger_forests_to_matrixRFModelterminalNodesweightedDistance
Dependencies:backportsbase64encbslibcachemcheckmatecliclustercodetoolscolorspacecowplotcpp11crayondata.tabledigestdplyrevaluatefansifarverfastmapfontawesomeforeignFormulafsgenericsggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglatticelifecyclelobstrmagrittrMASSMatrixMatrixModelsmemoisemgcvmimemultcompmunsellmvtnormnlmennetpillarpkgconfigpolsplineprettyunitspryrpurrrquantregR6rangerrappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelrlangrmarkdownrmsrpartrstudioapisandwichsassscalesSparseMstringistringrsurvivalTH.datatibbletidyrtidyselecttinytexutf8vctrsviridisviridisLitewithrxfunyamlzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Converts a distance vector into an object of class 'dist' | asDistObject |
| Call a function by character strings using the namespace and custom parameters. | call_function |
| Case Based Reasoning | CaseBasedReasoning |
| Root class for common functionality of this package | CBRBase |
| Cox-Beta Model for Case-Based-Reasoning | CoxModel |
| Depth Distance | depth_distance |
| Distance calculation based on RandomForest Proximity or Depth | distanceRandomForest |
| Number of Edges between Terminal Nodes | edges_between_terminal_nodes |
| Generate Grid | generate_grid |
| Linear Regression Model for Case-Based-Reasoning | LinearModel |
| Logistic Regression Model for Case-Based-Reasoning | LogisticModel |
| Get proximity matrix of an ranger object | proximity_distance |
| Forest2Matrix | ranger_forests_to_matrix |
| Root class for Regression Models, e.g., CPH, logistic, and linear regression | RegressionModel |
| RandomForest Model for Searching Similar Cases | RFModel |
| Get the terminal node id of a RandomForest Object | terminalNodes |
| Weighted Distance calculation | weightedDistance |
