Train a binary classification model on data in one or more Bioconductor objects

ID: B2AI_USECASE:38

Name: Train a binary classification model on data in one or more Bioconductor objects.

Description: Training a binary classification model on Bioconductor objects can be a convenient way to work with R statistical functions on large quantities of heterogeneous data. After any necessary preprocessing of the data, such as normalizing or filtering, split it into a training and test set. Then select a classification algorithm and use the training data to train a model. Test data may be used to evaluate the performance of the model and adjust any parameters as necessary.

Category: modeling

Involved in: Experimental Design

Data Topics:

• B2AI_TOPIC:5 (Data)

Contributor: Harry Caufield (ORCID:0000-0001-5705-7831)