search for: classifli

Hello, I am trying to explore a classification with GGobi. I am trying to generate additional data according to the model so I can draw the decision boundaries on the GGobi plot. The problem is that I always get the same error: Error in predict.lda(model,data): wrong number of variables, even if I know that I used the same number of variables for the model generation (6) and for the additional

The classifly package uses rggobi to visualise classification boundaries in high-dimensions. Given p-dimensional training data containing d groups (the design space), a classification algorithm (classifier) predicts which group new data belongs to. Generally the input to these algorithms is high dimensional, and the boundaries between groups will be high dimensional and perhaps curvilinear or

Hello useR, Could you please tell me how to draw the decision boundaries in a scatterplot of the original data for a LDA or Rpart object. For example: > library(rpart) >fit.rpart <- rpart(as.factor(group.id)~., data=data.frame(Data) ) How can I draw the cutting lines on the orignial Data? Or is there any built in functions that can read the rpart object 'fit.rpart' to do

Hello, I would like to plot the results of a LDA analysis plotting the discriminant scores with the decission boundaries on it with rggobi. I have GGobi already installed on my computer. I have three classes, so the plot would be LD1xLD2 plus the decission boundaries. Here there is the code I use make the plot: library(MASS) data <- zgcppr273K.pca$x[,1:7] Tumor <-