sits_svm: Train SITS classifier with a Support Vector Machine

In luizassis/sits: Satellite Image Time Series Analysis

Description

This function receives a tibble with a set of attributes X for each observation Y These attributes are usually distance metrics between patterns and observations This function is a front-end to the "svm" method in the "e1071" package. Please refer to the documentation in that package for more details.

Usage

sits_svm(distances.tb = NULL, formula = sits_formula_logref(),
  kernel = "linear", degree = 3, coef0 = 0, cost = 1,
  tolerance = 0.001, epsilon = 0.1, ...)

Arguments

distances.tb	a time series with a set of distance measures for each training sample
formula	a symbolic description of the model to be fit. SITS offers a set of such formulas (default: sits_svm)
kernel	the kernel used in training and predicting (options = linear, polynomial, radial basis, sigmoid)
degree	exponential of polynomial type kernel
coef0	parameter needed for kernels of type polynomial and sigmoid (default: 0)
cost	cost of constraints violation
tolerance	tolerance of termination criterion (default: 0.001)
epsilon	epsilon in the insensitive-loss function (default: 0.1)
...	other parameters to be passed to e1071::svm function

Value

result either an model function to be passed in sits_predict or an function prepared that can be called further to compute multinom training model

Author(s)

Alexandre Xavier Ywata de Carvalho, [e-mail]

Rolf Simoes, [e-mail]

luizassis/sits documentation built on May 30, 2019, 7:15 p.m.