Results

In this section you will find different ways to save the results generated by the data mining techniques implemented in bioScience.

Suppose you have an object called dataset in which both the original and preprocessed datasets are stored. In addition, you will have an object called listModels which stores the results of running a data mining technique. To see how to run a data mining technique, see Data mining section of this user guide.

Save the gene names

This subsection shows how to store the gene names of each result generated by the data mining techniques.

import bioscience as bs
bs.saveGenes(path="path/", models=listModels, data=dataset)

To understand the meaning of each attribute, you can access the API reference.

Saving the results of a data mining technique

This subsection shows how to save the complete results of any data mining technique that has been previously executed.

import bioscience as bs
bs.saveResults(path="path/", models=listModels, data=dataset)

To understand the meaning of each attribute, you can access the API reference.

Saving the results index of a data mining technique

This subsection shows how to save the row and column indices of each result generated by any data mining technique.

import bioscience as bs
bs.saveResultsIndex(path="path/", models=listModels)

To understand the meaning of each attribute, you can access the API reference.

Saving binary datasets

This subsection may be useful if the user has loaded a dataset and performed a binarisation in bioScience. Through this function we can store the binarised datasets.

import bioscience as bs
bs.saveBinaryDatasets(path="path/", datasets=dataset)

To understand the meaning of each attribute, you can access the API reference.