predict_optimal_parameters: Predict Optimal Parameters Using Trained Model (Use in...

In SlimR: Machine Learning-Assisted, Marker-Based Tool for Single-Cell and Spatial Transcriptomics Annotation

Predict Optimal Parameters Using Trained Model (Use in package)

Description

Applies the trained machine learning model to predict optimal parameters for the current dataset.

Usage

predict_optimal_parameters(model, dataset_features)

Arguments

model	Trained machine learning model (now a list with two models)
dataset_features	Extracted characteristics of current dataset

Value

List containing predicted min_expression and specificity_weight

See Also

Other Section_1_Functions_Use_in_Package: calculate_cluster_variability(), calculate_expression(), calculate_expression_skewness(), calculate_probability(), estimate_batch_effect(), extract_dataset_features(), generate_training_data(), postprocess_parameters(), train_parameter_model()

SlimR documentation built on Dec. 17, 2025, 5:09 p.m.