.sits_predict_interval

A data.table with distance values.

time

List with the raster objects for classification (values and probs).

output.lst

Machine learning model to be applied.

ml_model

labels

Integer values corresponding to labels.

int_labels

Initial row of the output layer to write block.

first_row

Number of cores to process the time series.

multicores

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.

.sits_predict_interval: Classify one interval of data

Description

Usage

Arguments

Value