visualize_threshold: Title

In eklavyaj/RandomSplitDiagnostics: The Package allows you to diagnose the randomness and model performance of a given train-test split in machine learning.

Title

Description

Title

Usage

visualize_threshold(
  dataset.name,
  d.vec,
  df.train,
  df.test,
  model.relation = "",
  initial.scores,
  alpha = 0.05,
  save.plots = TRUE,
  output.dir = "Output"
)

Arguments

dataset.name	Name of the Dataset (String)
d.vec	Vector containing the mahalanobis distance based metric across different train-test splits
df.train	Train Partition (R DataFrame)
df.test	Test Partition (R DataFrame)
model.relation	The relation used for regression model
initial.scores	The performance metric value for the given initial train-test split
alpha	The level of the test for visualize_threshold, default set to 0.05
save.plots	Saves plots in output.dir when set to TRUE
output.dir	The path to output directory the plots are saved to

eklavyaj/RandomSplitDiagnostics documentation built on June 1, 2022, 8:36 p.m.