get.score: Calculate score from each model to testing dataset. You can...

In PaoloBnn/Retip: Retention Time Prediction for Metabolomics

Calculate score from each model to testing dataset. You can also use training data or whole dataset. It accept untill 6 models

Description

Calculate score from each model to testing dataset. You can also use training data or whole dataset. It accept untill 6 models

Usage

get.score(t, m1, m2, m3, m4, m5, m6)

Arguments

t	A dataset with RT and Chemical Descriptors, like training or testing.
m1	a model previusly trained (XGBoost, BRNN, RF, Keras, Lightgbm or autoML)
m2	a model previusly trained (XGBoost, BRNN, RF, Keras, Lightgbm or autoML)
m4	a model previusly trained (XGBoost, BRNN, RF, Keras, Lightgbm or autoML)
m5	a model previusly trained (XGBoost, BRNN, RF, Keras, Lightgbm or autoML)
m6	a model previusly trained (XGBoost, BRNN, RF, Keras, Lightgbm or autoML)

Value

Returns score, RMSE, R2, MAE and 95 It is orderd by RMSE ascending so always you have best ranking model on top

Examples

stat <- get.score(testing, model_xgb, model_lightgbm, model_keras,
                  model_brnn, model_rf, model_h2o)

PaoloBnn/Retip documentation built on June 8, 2024, 6:19 a.m.