Feature selection
Feature selection is a preprocessing technique in spectroscopy that selects the most relevant features. The following algorithms are available:
The variable selection algorithms implemented in
chemotoolsallow you to select a subset of variables/features from the spectra. They are not designed to find the most relevant variables/features for a given task.
Range cut
Range cut by index is a preprocessing technique in spectroscopy that selects all the variables in the spectra given a range of either two indices or two wavenumbers.
Arguments:
| Argument | Description | Type | Default |
|---|---|---|---|
start | If not wavenumbers, start corresponds to the first index. If the wavenumbers are provided, then it correpsonds to the first wavenumber. | float | 0 |
end | If not wavenumbers, end corresponds to the last index. If the wavenumbers are provided, then it correpsonds to the last wavenumber. | float | -1 |
wavenumbers | The wavenumbers of the spectra. | numpy.ndarray/list | None |
The
wavenumbersvector must be sorted in ascending order.
Usage examples:
Case 1: Range cut by index
from chemotools.feature_selection import RangeCut
rcbi = RangeCut(0, 200)
spectra_rcbi = rcbi.fit_transform(spectra)
Case 2: Range cut by wavenumbers
from chemotools.feature_selection import RangeCut
rcbw = RangeCut(950, 1100, wavenumbers=wn)
spectra_rcbw = rcbw.fit_transform(spectra)
After fitting the method with the wavenumbers, the selected wavenumbers can be accessed using the wavenumbers_ attribute.
Plotting example:
Index selector
IndexSelector is a preprocessing technique in spectroscopy that selects the most relevant variables. The selected features do not need to be continuous in the spectra, but they can be located at different locations. The algorithm allows selecting the features by imputing a list of indices or wavenumbers.
Arguments:
| Argument | Description | Type | Default |
|---|---|---|---|
features | The indices or wavenumbers of the features to be selected. If None it will return the entire array. | numpy.ndarray/list | None |
wavenumbers | The wavenumbers of the spectra. | numpy.ndarray/list | None |
The
wavenumbersvector must be sorted in ascending order.
Usage examples:
In the example below, the selected wavenumbers wn_select are used to select the features in the spectra.The selected wavenumbers include features from the beginning, middle and end of the spectra.
from chemotools.feature_selection import IndexSelector
sfbw = IndexSelector(features=wn_select,wavenumbers=wn)
spectra_sfbw = sfbw.fit_transform(spectra)