init for drifter

.Rbuildignore

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+^.*\.Rproj$
+^\.Rproj\.user$

.gitignore

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 # Shiny token, see https://shiny.rstudio.com/articles/shinyapps.html
 rsconnect/
+.Rproj.user

DESCRIPTION

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+Package: drifter
+Title: Concept Drift and Concept Shift Detection for Predictive Models
+Version: 0.1
+Authors@R: person("First", "Last", email = "first.last@example.com", role = c("aut", "cre"))
+Description: What the package does (one paragraph).
+Depends: R (>= 3.5.0)
+License: GPL
+Encoding: UTF-8
+LazyData: true

NAMESPACE

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+# Generated by roxygen2: fake comment so roxygen2 overwrites silently.
+exportPattern("^[^\\.]")

README.md

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-# drifter
-Concept Drift and Concept Shift Detection for Predictive Models
+# drifter: Concept Drift and Concept Shift Detection for Predictive Models
+
+Machine learning models are often fitted and validated on historical data under silent assumption that data are stationary. The most popular techniques for validation (k-fold cross-validation, repeated cross-validation, and so on) test models on data with the same distribution as training data.
+
+Yet, in many practical applications, deployed models are working in a changing environment. After some time, due to changes in the environment, model performance may degenerate, as model may be less reliable.
+
+Concept drift refers to the change in the data distribution or in the relationships between variables over time. Think about model for energy consumption for a school, over time the school may be equipped with larger number of devices of with more power-efficient devices that may affect the model performance.
+
+

drifter.Rproj

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+Version: 1.0
+
+RestoreWorkspace: No
+SaveWorkspace: No
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: knitr
+LaTeX: pdfLaTeX
+
+AutoAppendNewline: Yes
+StripTrailingWhitespace: Yes
+
+BuildType: Package
+PackageUseDevtools: Yes
+PackageInstallArgs: --no-multiarch --with-keep.source
+PackageRoxygenize: rd,collate,namespace