sits_formula_logref

<p>Index of the valid columns
to compose formula (default: -2:0).</p>

predictors_index

<p>A function to be used as a symbolic description
of some fitting models such as svm and random forest.
This function tells the models to do a log transformation of the inputs.
The `predictors_index` parameter informs
the positions of `tb` fields corresponding to formula independent variables.
If no value is given, the default is NULL,
a value indicating that all fields will be used as predictors.</p>

A set of tools for working with satellite image time series, both as individual data or as part of data cubes.
Builds data cubes from collections in AWS, Brazil Data Cube, and Digital Earth Africa.
Provides different visualisation methods for image time series.
Provides smoothing methods for noisy time series.
Includes functions for smoothing based on Bayesian inference.
Enables different clustering methods, including dendrograms and self-organized maps (SOM).
Matches noiseless patterns with noisy time series using the time-weighted dynamic time warping (TWDTW) method for shape recognition.
Provides machine learning methods for time series classification, including support vector machines (SVM), random forests and deep learning.
Minimum recommended requirements: 8 GB RAM and 1 CPU dual-core.

Gilberto Camara

sits

Satellite Image Time Series Analysis for Remote Sensing Data Cubes

Rolf Simoes

Felipe Souza

Lorena Santos

Alexandre Carvalho

Pedro Andrade

Karine Ferreira

Alber Sanchez

Gilberto Queiroz

sits_formula_logref function

Define a loglinear formula for classification models — sits_formula_logref

Define a loglinear formula for classification models

sits_formula_logref: Define a loglinear formula for classification models

Description

Usage

Arguments

Value