Prerequisites

library(multree)

Intro

Goal

  • Construct a neural decision forest using the multree package.

Conclusion

  • The multree can used on raw signals.

Outline

  • Prep Data
  • Train model
  • Predict
  • Inspect

Data - Signals

Hand Extension Recording

Matrix

home <- "DavidHolds"
hand.ext <- read.table("DavidHolds/Extension_1", sep= ",")[, c(4:10, 3)]
head(hand.ext)
##   emg.sig1 emg.sig2 emg.sig3 emg.sig4 emg.sig5 emg.sig6 emg.sig7 emg.sig8
## 1       -2       -6       -1      -31       19      -25       -8       -3
## 2        4        8        6       36       17        0        3        3
## 3       -2       -3       14       98      114       37        3        2
## 4        0        5        9       20        0       10        2        2
## 5        2        1      -15      -76      -63      -28       -7       -1
## 6        4        6        6       -4     -110       -4        5        4

Vectorized

v <- do.call(c, hand.ext)
plot(1:length(v), v)
abline(v=1:7*50, col = "red")