lucky_odds: Quickly apply stanger full process flow to flag candidates...
In stranger: Simple Toolkit in R for ANomalies Get, Explain and Report

Description Usage Arguments Selecting variables

lucky_odds is basically a wrapper around the process: add_id –> crazyfy –> strange (weird method with set of parameters) –> singularize (default parameters: all methods) –> get_anomalies (flag top n.anom anomalies) –> fortify to enrich source data. By calling lucky_odds, analyst gets back source data with an additional column flagging some records. Though obviously simplifying the analysis process, not all options are available and intermediate objects are not available for further analysis.

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lucky_odds(data, n.anom = 5, ..., analysis.drop = NULL,
  analysis.keep = NULL, weird = "knn", stack = "avg",
  stack.method = "norm")

`data`	Source data (data.frame or data.table).
`n.anom`	Number of anomaly candidate records to flags.
`...`	Additional parameters to be passed to weird method (`analysis.method`).
`analysis.drop`	Character - set of variables to be removed from analysis (metrics computations by weird).
`analysis.keep`	Character - set of variables to be kept for analyis (metrics computations by weird).
`weird`	weird method to use for metric computation
`stack`	Stacking metric passed to `get_anomalies`.
`stack.method`	Stacking selection method passed to `get_anomalies`.

If your source data contains variables you don't want to use in metrics computations - weird method: knnw, autoencode..., then you have to first select analysis variables. You can thos this use either analysis.keep OR analysis.drop. Those two parameters are mutually exclusive. library(stranger) data(iris) anomalies <- lucky_odds(iris[,1:4]) table(anomalies$flag_anomaly)

stranger documentation built on March 18, 2018, 2:01 p.m.