condense {class} | R Documentation |

## Condense training set for k-NN classifier

### Description

Condense training set for k-NN classifier

### Usage

```
condense(train, class, store, trace = TRUE)
```

### Arguments

`train` |
matrix for training set |

`class` |
vector of classifications for test set |

`store` |
initial store set. Default one randomly chosen element of the set. |

`trace` |
logical. Trace iterations? |

### Details

The store set is used to 1-NN classify the rest, and misclassified patterns are added to the store set. The whole set is checked until no additions occur.

### Value

Index vector of cases to be retained (the final store set).

### References

P. A. Devijver and J. Kittler (1982)
*Pattern Recognition. A Statistical Approach.*
Prentice-Hall, pp. 119–121.

Ripley, B. D. (1996)
*Pattern Recognition and Neural Networks.* Cambridge.

Venables, W. N. and Ripley, B. D. (2002)
*Modern Applied Statistics with S.* Fourth edition. Springer.

### See Also

### Examples

```
train <- rbind(iris3[1:25,,1], iris3[1:25,,2], iris3[1:25,,3])
test <- rbind(iris3[26:50,,1], iris3[26:50,,2], iris3[26:50,,3])
cl <- factor(c(rep("s",25), rep("c",25), rep("v",25)))
keep <- condense(train, cl)
knn(train[keep, , drop=FALSE], test, cl[keep])
keep2 <- reduce.nn(train, keep, cl)
knn(train[keep2, , drop=FALSE], test, cl[keep2])
```

[Package

*class*version 7.3-22 Index]