# Results toolbox

## Restools

*Current version is 1.7.0 (Feb. 2013)*.

This toolbox is a general toolbox for Matlab that should make it simpler to collect experimental results, annotate them, plot/print/show them in countless formats (like graphs, text tables, latex tables, html tables, bar graphs, surface graphs) and store them.

For this a new Matlab object 'results' is created. The idea of the results-object is:

- To extend the Matlab matrix with 'feature annotations', such that printing a matrix also shows the meaning of each row and column
- To be able to print the content of a matrix consistently in different formats (like text, latex, html, in a graph, a bar graph, etc)
- To extend the averaging over a dimension such that significantly different entries in a matrix are highlighted, and such that missing values (=NaN's) are handled correctly

The results-object should be as similar as possible to the standard Matlab matrix object ('double').

### Download restools

Version **restools 1.7.0** can be downloaded here.

### Example

For the full details on how to use the toolbox, several example files are included in the toolbox. Please have a look at, for instance, the following script:

% This script should show how a results-object can be created, and how % to make nice tables and figures form it. % Generate (not completely random) results to show: m = repmat((1:10)'/10,[1,4,5]); res = m + 0.4*rand(10,4,5); % Define the values of the different dimensions: dim1 = {'cl1','cl2','cl3','cl4','cl5','cl6',... 'cl7','cl8','cl9','cl10'}; dim2 = {'data1','iris','ionosphere','dat4'}; dim3 = (1:5)'; % Store it in a results object: R = results(res,dim1,dim2,dim3); % Set the dimension names: R = setdimname(R,'classifiers','datasets','runs'); % Set the results name: R = setname(R,'AUC performances'); % Average over the runs (dimension 3), and find the minima in each % column (minimum over dimension 1): T = average(10*R,3,'min1'); % And finally show the results, in text and html: show(T) show(T,'html'); show(T,'graph')

The commands in the last row of this script generates the following HTML-table and graph:

classifiers | datasets | |||
---|---|---|---|---|

data1 | iris | ionosphere | dat4 | |

cl1 | 3.0 (1.2) | 1.9 (0.5) | 3.4 (1.1) | 3.7 (0.9) |

cl2 | 4.8 (1.1) | 4.4 (1.5) | 3.6 (1.2) | 3.0 (1.3) |

cl3 | 4.4 (1.3) | 5.5 (1.2) | 5.2 (1.0) | 5.2 (1.2) |

cl4 | 6.7 (0.8) | 5.4 (1.2) | 6.3 (1.1) | 6.1 (1.6) |

cl5 | 7.1 (1.5) | 6.6 (1.7) | 7.3 (1.1) | 6.7 (1.3) |

cl6 | 7.5 (1.3) | 6.9 (0.6) | 8.1 (1.5) | 8.2 (1.0) |

cl7 | 9.0 (1.4) | 9.8 (0.9) | 8.7 (0.8) | 8.8 (0.8) |

cl8 | 10.6 (0.8) | 10.4 (0.9) | 9.5 (1.0) | 10.4 (1.4) |

cl9 | 11.3 (1.1) | 11.1 (1.2) | 11.0 (1.2) | 11.3 (1.4) |

cl10 | 12.5 (1.4) | 11.7 (1.3) | 11.2 (1.0) | 11.5 (1.2) |