How to plot a curve to separate data?

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How to plot a curve to separate data?

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#1 by (4 votes)

1

I'm testing some things in the language and this question came to me. I made a program that has a database that is divided into two groups (Group 1 and Group 2) and its elements are already labeled. I want to classify a new group of elements based on the Euclidean distance between each of its elements and those of the group that are already labeled.

What I've said is already working perfectly and I'm plotting the graph with the two groups. However, I do not know how to draw a curve that separates one group from the other.

The way I'm doing it looks like this:

Hereisthecodeformyattempt:

library('mvtnorm')library('class')library('plot3D')#calculaadistanciaentrecadapontonovoetodososdetreinamentocalcula_dist<-function(elementos_novos,elementos_treinamento){matriz_distancia<-matrix(0,nrow(elementos_novos),ncol=nrow(elementos_treinamento))for(iin1:nrow(elementos_novos)){for(jin1:nrow(elementos_treinamento)){matriz_distancia[i,j]<-sqrt(sum((elementos_novos[i,]-elementos_treinamento[j,])^2))}}return(matriz_distancia)}#buscapeloskvizinhosmaisproximos,verificaqualéorotulomaispresenteeatribuiaoelementonovorotula_elementos<-function(elementos_treinamento,elementos_novos,rotulos_treinamento,num_vizinhos){matriz_distancia<-calcula_dist(elementos_novos,elementos_treinamento)rotulos<-matrix(0,nrow=nrow(elementos_novos),ncol=1)for(iin1:nrow(rotulos)){qtd_verdadeiro<-0qtd_falso<-0dados<-data.frame(matriz_distancia[i,],rotulos_treinamento)ind<-order(dados$matriz_distancia.i...)vizinhos_mais_proximos<-Y[ind[1:num_vizinhos]]for(jin1:num_vizinhos){if(vizinhos_mais_proximos[j]==1)qtd_verdadeiro<-qtd_verdadeiro+1elseqtd_falso<-qtd_falso+1}if(qtd_verdadeiro>qtd_falso)rotulos[i]<-1elseif(qtd_verdadeiro<qtd_falso)rotulos[i]<-2}return(rotulos)}#geraosdadosdosconjuntos1e2conjunto1<-rmvnorm(100,mean=c(3,3),sigma=matrix(c(6,0,0,2),nrow=2,byrow=T))conjunto2<-rmvnorm(100,mean=c(2,-2),sigma=matrix(c(10,0,0,0.5),nrow=2,byrow=T))#criaumsógrupoparaoselementosdetreinamentoelementos<-rbind(conjunto1,conjunto2)#geraorotuloparaoselementosrotulos<-c(rep(1,100),rep(0,100))#repeteomesmoprocessoparaosconjuntosdetesteconjunto_teste1<-rmvnorm(50,mean=c(3,3),sigma=matrix(c(6,0,0,2),nrow=2,byrow=T))conjunto_teste2<-rmvnorm(50,mean=c(2,-2),sigma=matrix(c(10,0,0,0.5),nrow=2,byrow=T))elementos_teste<-rbind(conjunto_teste1,conjunto_teste2)plot3D::scatter2D(conjunto_teste1[,1],conjunto_teste1[,2],col="black", pch = 111, cex = 1, xlim = c(-7,7), ylim = c(-6,6))
plot3D::scatter2D(conjunto_teste2[,1], conjunto_teste2[,2], col = "red", pch = 43, cex = 1, add = TRUE)


dados <- data.frame(X,Y)
rotulos_euclidiana <- rotula_elementos(elementos , elementos_teste, rotulos, 3)

#se o rotulo for 1, class recebe TRUE, se não, recebe FALSE
class <- (1 == rotulos_euclidiana)
par(new=T)

plot(class,cex = 20, type='l', col='black')

I was trying to use contour also but it asks for an array and I do not know what array I could play there.

r plot

asked by anonymous 14.06.2017 / 23:41

1 answer

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score 4 · Accepted Answer

Solution Attempt:

Step 1: Generate the data

# pacotes
library(tidyverse)
library(mvtnorm)
# reprodutibilidade
set.seed(10)
# observações
N <- 1000
# lista de parâmetros
parms <- list(
  a = list(mu = c(0, 0), sigma = matrix(c(4, 2, 2, 4), nrow = 2)),
  b = list(mu = c(5, 5), sigma = matrix(c(4, -2, -2, 4), nrow = 2))
)
# cria base de dados
dados <- parms %>% 
  map_df(~as_tibble(rmvnorm(1000, .x$mu, .x$sigma)), .id = 'y')

the table looks like this:

> head(dados)
# A tibble: 6 x 3
      y         V1          V2
  <chr>      <dbl>       <dbl>
1     a -1.3003304 -3.31843274
2     a -1.2522601 -2.68292404
3     a  1.0809874  4.10785510
4     a  0.9412994  0.43563123
5     a  2.9512012  1.15567989
6     a  0.3998171 -0.04013559

The graph looks like this:

dados %>% 
  ggplot(aes(x = V1, y = V2, colour = y, type = y)) +
  geom_point()

Step2:FitTemplate

OnemodelyoucanusetoseparatethedataisDiscriminantAnalysis,usingtheldafunction.So:

m_lda<-MASS::lda(y~V1+V2,data=dados)

Step3:Drawretinha

Itookthecodetodrawtheline this link .

First you need to create a data grid and get ratings for the entire grid:

dados_grid <- dados %>% 
  dplyr::select(-y) %>% 
  # para cada variável, uma sequência de tamanho 10 entre o mínimo e o máximo
  map(~{
    r <- range(.x)
    seq(r[1], r[2], length.out = 10)
  }) %>% 
  # monta a grid
  cross_df() %>% 
  # adiciona as predições (1 ou 2)
  mutate(y = as.numeric(predict(m_lda, newdata = .)$class))

Lastly, use geom_countour() to add the retinha. The parameter breaks= was chosen between 1 and 2 on purpose to draw the retinha exactly in the place we want (without this parameter, you would see several retinhas, which are the level curves generated by this grid).

The result looks like this:

dados %>% 
  ggplot(aes(x = V1, y = V2, colour = y, type = y)) +
  geom_point() +
  geom_contour(aes(z = y), data = dados_grid, breaks = 1.5)

EDIT:

Foryoutobetterseewhatthisdamn%isdoing(increasingthenumberofpointsto30*30):

dados_grid<-dados%>%dplyr::select(-y)%>%map(~{r<-range(.x)#aumenteipara30norangeaqui!!!!!!!!!!!!!!!!!seq(r[1],r[2],length.out=30)})%>%cross_df()%>%mutate(y=as.numeric(predict(m_lda,newdata=.)$class))dados%>%ggplot(aes(x=V1,y=V2,colour=y))+geom_point()+geom_contour(aes(z=y),data=dados_grid,breaks=1.5)+theme_minimal()+#desenhapontosdagridgeom_point(aes(shape=as.character(y),colour=NULL),alpha=.3,size=3,data=dados_grid)+scale_shape_manual(values=c('+','o'))