.sits_check_classify_params

Vector of file names to store the output (one file per classified year).

file

Tibble with information about a set of space-time raster bricks.

coverage

An R model trained by <code><a rd-options="sits" href="/link/sits_train?package=sits&version=1.12.0&to=sits" data-mini-rdoc="sits::sits_train">sits_train</a></code>.

ml_model

Verify that required parameters are correct.

A set of tools for working with satellite image time series.
Supports data retrieval from a WTSS (web time series service) and other data sets.
Provides different visualisation methods for image time series.
Provides smoothing methods for noisy time series.
Enables different clustering methods, including dendrograms and SOM.
Matches noiseless patterns with noisy time series using the TWDTW method for shape recognition.
Provide machine learning methods for time series classification, including SVM, LDA, QDA, GLM, Lasso, Random Forests and Deep Learning.

Pedro Andrade

sits

Satellite Image Time Series Analysis

Rolf Simoes

Gilberto Camara

Victor Maus

Alexandre Carvalho

Lorena Santos

Gilberto Queiroz

Alber Sanchez

Luiz Assis

Adeline Marinho

.sits_check_classify_params function

An R model trained by <code><a rd-options='sits' href='sits_train'>sits_train</a></code>.

.sits_check_classify_params: Check clasification parameters

Description

Usage

Arguments

Value