AdaptiveNormalizer: One-pass Adaptive Normalizer

In alaineiturria/otsad: Online Time Series Anomaly Detectors

One-pass Adaptive Normalizer

Description

R6 class with our adaptation of the method proposed by Ogasawara et al. for one-pass online time-series adaptive normalization. This method is designed to train neural networks and returns the normalized train and test feature sets. In this proposal, the outlier elimination phase has been omitted.

Methods

Public methods

• AdaptiveNormalizer$new()

• AdaptiveNormalizer$normalize()

• AdaptiveNormalizer$denormalize()

---

Method new()

Create a new AdaptiveNormalizer object.

Usage

AdaptiveNormalizer$new(wl = 10, maxmin = T, l = 3, returnPoint = F)

Arguments

wl

Length of the window with historical data values.

maxmin

If TRUE standardization and normalization are applied, else only standardization is applied.

l

Times IQR to anomaly removing. It must be a number greater than 0. By default 3, but other common values could be 1.5 and 6.

returnPoint

If FALSE normalized then the current window is returned, else, the normalized current data point is returned.

Returns

A new AdaptiveNormalizer object.

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Method normalize()

Normalizes the current data value.

Usage

AdaptiveNormalizer$normalize(x)

Arguments

x

Current data value to be normalized.

Returns

If returnPoint = FALSE then normalized current train and test windows are returned, else, normalized current data point is returned.

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Method denormalize()

Denormalizes the current data value.

Usage

AdaptiveNormalizer$denormalize(y)

Arguments

y

Current data value to be denormalized.

Returns

Denormalized current data point.

References

E. Ogasawara, L. C. Martinez, D. De Oliveira, G. Zimbrão, G. L. Pappa,M. Mattoso, Adaptive Normalization: A novel data normalization ap-proach for non-stationary time series, in: Proceedings of the International Joint Conference on Neural Networks, 2010, pp. 1-8

Examples

normalizer <- AdaptiveNormalizer$new(3)

normalizer$normalize(10)
normalizer$normalize(15)
normalizer$normalize(20)
normalizer$normalize(10)
normalizer$normalize(30)
normalizer$normalize(15)

normalizer$denormalize(-0.4858841)

alaineiturria/otsad documentation built on Jan. 12, 2023, 12:26 p.m.