Kira (version 1.0.6)

regression: Linear regression supervised classification method

Description

Performs supervised classification using the linear regression method.

Usage

regression(train, test, class, intercept = TRUE)

Value

predict

The classified factors of the test set.

Arguments

train

Data set of training, without classes.

test

Test data set.

class

Vector with data classes names.

intercept

Consider the intercept in the regression (default = TRUE).

Author

Paulo Cesar Ossani

References

Charnet, R. at al. Analise de modelos de regressao lienar, 2a ed. Campinas: Editora da Unicamp, 2008. 357 p.

Rencher, A. C. and Schaalje, G. B. Linear models in statisctic. 2th. ed. New Jersey: John & Sons, 2008. 672 p.

Rencher, A. C. Methods of multivariate analysis. 2th. ed. New York: J.Wiley, 2002. 708 p.

See Also

plot_curve and results

Examples

data(iris) # data set

data  <- iris
names <- colnames(data)
colnames(data) <- c(names[1:4],"class")

#### Start - hold out validation method ####
dat.sample = sample(2, nrow(data), replace = TRUE, prob = c(0.7,0.3))
data.train = data[dat.sample == 1,] # training data set
data.test  = data[dat.sample == 2,] # test data set
class.train = as.factor(data.train$class) # class names of the training data set
class.test  = as.factor(data.test$class)  # class names of the test data set
#### End - hold out validation method ####

r <- (ncol(data) - 1)
res <- regression(train = data.train[,1:r], test = data.test[,1:r], 
                  class = class.train, intercept = TRUE)

resp <- results(orig.class = class.test, predict = res$predict)

message("Mean squared error:"); resp$mse
message("Mean absolute error:"); resp$mae
message("Relative absolute error:"); resp$rae
message("Confusion matrix:"); resp$conf.mtx  
message("Hit rate: ", resp$rate.hits)
message("Error rate: ", resp$rate.error)
message("Number of correct instances: ", resp$num.hits)
message("Number of wrong instances: ", resp$num.error)
message("Kappa coefficient: ", resp$kappa)
message("General results of the classes:"); resp$res.class