What types of Datasets does PyBrain offer
This recipe explains what types of Datasets does PyBrain offer
Recipe Objective - What types of Datasets does PyBrain offer?
Datasets are data that is available for testing, validation, and training in networks. There are two types of datasets in Pybrain.
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Table of Contents
1. SupervisedDataSet:
The SupervisedDataSet consists of input and target fields. It is the simplest form of data set and is used primarily for supervised learning tasks.
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Here's how you can use it in your code:
from pybrain.datasets import SupervisedDataSet
2. ClassificationDataSet:
This data set is used primarily to solve classification problems. It accepts input, target field, and an additional field called "Class," an automatic backup of the specified targets. For example, the output is 1 or 0, or the output is grouped with values based on the given inputs; it belongs to a certain class.
Here's how you can use it in your code:
from pybrain.datasets import ClassificationDataSet
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