Description Usage Arguments Details Value Author(s) Examples

View source: R/correlationHC.details.R

To explain how the hierarchical correlation algorithm works.

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`data` |
is a data frame with the main data. |

`target` |
is a data frame , a numeric vector or a matrix. Default value = NULL. |

`weight` |
is a numeric vector. Default value = empty vector. |

`distance` |
is a string. The distance type. Default value = Euclidean distance. |

`normalize` |
is a boolean parameter. If the user wants to normalize weights. Default value = TRUE. |

`labels` |
is a string vector. For the graphical solution. Default value = NULL. |

This function explains the complete hierarchical correlation method. It explains the theoretical algorithm step by step.

1 - The function transforms data in useful object to be used.

2 - It creates the clusters.

3 - It calculates the distance from the target to every cluster applying the distance type given.

4 - It orders the distance in an increasing way.

5 - It orders the clusters according to their distance from the previous step

6 - It shows the clusters sorted and the distance used.

R object with a dendrogram, the sorted distances and the list with every cluster. Explanation.

Roberto Alcántara roberto.alcantara@edu.uah.es

Juan José Cuadrado jjcg@uah.es

Universidad de Alcalá de Henares

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data <- matrix(c(1,2,1,4,5,1,8,2,9,6,3,5,8,5,4),ncol= 3)
dataFrame <- data.frame(data)
target1 <- c(1,2,3)
target2 <- dataFrame[1,]
weight1 <- c(1,6,3)
weight2 <- c(0.1,0.6,0.3)
correlationHC.details(dataFrame, target1)
correlationHC.details(dataFrame, target1, weight1)
correlationHC.details(dataFrame, target1, weight1, normalize = FALSE)
correlationHC.details(dataFrame, target1, weight2, 'CAN', FALSE)
``` |

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