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CaseBasedReasoning (version 0.4.1)

Case Based Reasoning

Description

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) .

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install.packages('CaseBasedReasoning')

Monthly Downloads

128

Version

0.4.1

License

MIT + file LICENSE

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Maintainer

Dr. Mueller

Last Published

February 27th, 2026

Functions in CaseBasedReasoning (0.4.1)

summary.CoxModel

Summary method for CoxModel
print.CoxModel

Print method for CoxModel
print.LinearModel

Print method for LinearModel
proximity_distance

Get proximity matrix of an ranger object
ranger_forests_to_matrix

Forest2Matrix
summary.LogisticModel

Summary method for LogisticModel
summary.RFModel

Summary method for RFModel
predict.RFModel

Predict method for RFModel
predict.CoxModel

Predict method for CoxModel
predict.LinearModel

Predict method for LinearModel
asDistObject

Converts a distance vector into an object of class dist
LogisticModel

Logistic Regression Model for Case-Based-Reasoning
CaseBasedReasoning-package

CaseBasedReasoning: Case Based Reasoning
depth_distance

Depth Distance
RFModel

RandomForest Model for Searching Similar Cases
distanceRandomForest

Distance calculation based on RandomForest Proximity or Depth
LinearModel

Linear Regression Model for Case-Based-Reasoning
CoxModel

Cox-Beta Model for Case-Based-Reasoning
predict.LogisticModel

Predict method for LogisticModel
generate_grid

Generate Grid
edges_between_terminal_nodes

Number of Edges between Terminal Nodes
summary.LinearModel

Summary method for LinearModel
terminalNodes

Get the terminal node id of a RandomForest Object
weightedDistance

Weighted Distance calculation
RegressionModel

Root class for Regression Models, e.g., CPH, logistic, and linear regression
CBRBase

Root class for common functionality of this package
print.LogisticModel

Print method for LogisticModel
print.RFModel

Print method for RFModel