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v0.1.11-pre

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Refactor residuals (#144)

* update  attributes in ModelResidualBase

* update hotelling t2 residuals

* upadte interface in Q residuals

* update all interfaces in outlier algorithms

* remove depricated class

* refactor _utils into _base

* refactor useful  residual funcitons to utils

* rename functions

* fix typing error

* update functions in residual analysis

* format with with ruff

* refactor residual x calculation in dmodx

* change default method in qresiduals to "jackson-mudholkar"

* normalize dmodx by SPE in training and DoF

* format document with ruff

* Update chemotools/outliers/leverage.py

Swap order in inputs for calculate residuals

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update studentized_residuals.py

update intialization of the studentized_residuals

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Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

v0.1.10

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Feature/add metrics (#137)

* add residuals

* add leverage function

* format with ruff

* format with ruff

* add leverage and studentized residuals

* add tests for residuals

* test outliers parametrizing

* linter with ruff

* format document with ruff

* factor out functions from _base to utils

* rename modeltype to modeltypes

* rename utils to _utils

* facrtor out validate confidence from _base to _utils

* factor out validate and extract model

* fix implementation in dmodx outlier detection

* Update Hotelling T2

* update hotelling t2 model

* format documents by ruff

* finish hotelling, dmodx and q residuals

* add test for leverage

* update interfaces and add studentized Q residuals

* finish implementation of studentized residuals

v0.1.9

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Feature/augmentation add fractional padding (#136)

* add fractional shift

* add formatting

v0.1.8

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Feature/fix augmentation noise (#133)

* Unify add noise and add unit tests

* remove old noise functions

* rename old files with _ appended

* fis imports in testing

v0.1.7

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format tests

v0.1.6

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update python release to pypi

v0.1.5

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fix type

v0.1.4

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rangecut implements wavenumbers_ when cut

v0.1.3

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Update sklearn api (#60)

* update interface in air_pls

* update airpls

* update arpls api

* fix documentation in index_selector

* fix typo in index_selector

* fix api in constant baseline correction

* update cubic splines

* update api in linear correction

* update init for linear correction

* fix api in non negative

* fix api in polynomial and in subtract reference

* fix norris williams

* fix api in savitzky golay

* fix minmax scaler

* fix norm scaler

* fix point scaler

* fix emsc

* update msc

* update rnv

* update snv

* update mean filter

* update median filter

* update savgol filter

* update whittaker

v0.1.2

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Feature selection (#59)

* change module name to feature_selection

* add range_cut_selector

* update tests for rangecut selector

* refactor range cut selector

* Add index selector

* test index selector

* Remove old range_cut and select_features

* upate depricated np.matrix by standard np.array, and adjust code accordingly

* rename funcitons in feature selection to follow sklearn
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