.sits_classify_distances

distances_DT

class_info.tb

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

number of threads to process the time series.

multicores

Returns a sits tibble with the results of the ML classifier.

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_classify_distances function

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

Classify a distances tibble using machine learning models — .sits_classify_distances

Classify a distances tibble using machine learning models

.sits_classify_distances: Classify a distances tibble using machine learning models

Description

Usage

Arguments

Value