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datadriftR

CRAN status License: MIT

datadriftR is an R package for detecting data drift in streaming data. It monitors when statistical properties of your data change over time, which is essential for maintaining machine learning model performance in production.

Available Methods

Method Description
ddm Drift Detection Method
eddm Early Drift Detection Method
hddm_a Hoeffding’s bound with averaging
hddm_w Hoeffding’s bound with weighting
kswin Kolmogorov-Smirnov Windowing
adwin ADaptive WINdowing
page_hinkley Page-Hinkley Test
kl_divergence KL Divergence
profile_difference Profile Difference

Installation 

# Install from CRAN
install.packages("datadriftR")

# Or install the development version from GitHub with pak
# install.packages("pak")
pak::pak("ugurdar/datadriftR")

# Or install the development version from GitHub with remotes
# install.packages("remotes")
# remotes::install_github("ugurdar/datadriftR")

Documentation: https://ugurdar.github.io/datadriftR

Simple DDM Example 

library(datadriftR)

# Create a stream with drift at position 501
set.seed(123)
stream <- c(

  sample(c(0, 1), 500, replace = TRUE, prob = c(0.7, 0.3)),
  sample(c(0, 1), 500, replace = TRUE, prob = c(0.3, 0.7))
)

# Detect drift
results <- detect_drift(stream, method = "ddm")
print(results)

Documentation

Citation 

@article{dar2025datadriftr,
  title={datadriftR: Drift Detection Methods for Stream Data},
  author={Dar, Ugur and Cavus, Mustafa},
  journal={Journal of Open Source Software},
  year={2025}
}

Authors