Binary Dataset

versión 1.0 (4.04 KB) por Kepeng Qiu
MATLAB code for 2D or 3D binary dataset for classification.

13 descargas

Actualizada 13 May 2022

De GitHub

Ver licencia en GitHub

🔥🔥 BinaryDataset

MATLAB code for 2D or 3D binary dataset.

✨ MAIN FEATURES

  • 2D or 3D binary dataset of "banana" and "circle" shapes.
  • Partitioning of training dataset/label and test dataset/label.

🔨 HOW TO USE

ocdata = BinaryDataset();
[data, label] = ocdata.generate;
[trainData, trainLabel, testData, testLabel] = ocdata.partition;

The full Name-Value Arguments of class BinaryDataset are

  • shape: shape of dataset, 'banana' or 'circle'.
  • dimensionality: dimensionality of dataset, 2 or 3.
  • number: number of samples per class, for example: [200, 200].
  • display: visualization, 'on' or 'off'.
  • noise: noise added to dataset with range [0, 1]. For example: 0.2.
  • ratio: ratio of the test set with range (0, 1). For example: 0.3.

👉 Example 1

Generate a 3D banana-shaped dataset with 200 and 100 samples for each class, and divide 10% of the data into the test dataset.

ocdata = BinaryDataset( 'shape', 'banana',...
                        'dimensionality', 3,...
                        'number', [200, 100],...
                        'display', 'on', ...
                        'noise', 0.2,...
                        'ratio', 0.1);
[data, label] = ocdata.generate;
[trainData, trainLabel, testData, testLabel] = ocdata.partition;

👉 Example 2

Generate a 2D circle-shaped dataset with 100 and 300 samples for each class, and divide 50% of the data into the test dataset.

ocdata = BinaryDataset( 'shape', 'circle',...
                        'dimensionality', 2,...
                        'number', [100, 300],...
                        'display', 'on', ...
                        'noise', 0.2,...
                        'ratio', 0.5);
[data, label] = ocdata.generate;
[trainData, trainLabel, testData, testLabel] = ocdata.partition;

Citar como

Kepeng Qiu (2022). Binary Dataset (https://github.com/iqiukp/BinaryDataset/releases/tag/v1.0), GitHub. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2022a
Compatible con la versión R2016b y siguientes
Compatibilidad con las plataformas
Windows macOS Linux
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Para consultar o informar de algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.
Para consultar o informar de algún problema sobre este complemento de GitHub, visite el repositorio de GitHub.