Yes, it works! Thanks a lot! Now, i have another question...
When i try to use the tree for predict the value of the class with the
function "predict" the result is not a vector with TRUE or FALSE value (that
is what i want for every row of my test set) but is a sort of matrix with a
weight on the two possible values.
For better understanding, I copy the commands and the result.
I have two data frames, echoknn.train for growing the tree and echoknn.test
for testing it, there is the str() result
> str(echoknn.test)
'data.frame': 32 obs. of 6 variables:
$ age.at.heart.attack : num 55 57 68 60 54 55 66 54 55 55 ...
$ pericardical.effusion: int 0 0 0 0 0 1 0 0 0 1 ...
$ fractional.shortening: num 0.26 0.16 0.26 0.33 0.14 ...
$ epss : num 4 22 5 8 13 ...
$ lvdd : num 3.42 5.75 4.31 5.25 4.49 ...
$ wall.motion.index : num 1 2.25 1 1 1.19 ...
> str(echoknn.train)
'data.frame': 64 obs. of 7 variables:
$ age.at.heart.attack : num 70 65 51 62 63 46 63 70 79 59 ...
$ pericardical.effusion: int 1 0 0 0 1 0 0 1 0 0 ...
$ fractional.shortening: num 0.27 0.36 0.16 0.15 0.241 ...
$ epss : num 4.7 8.8 13.2 0 10 ...
$ lvdd : num 4.49 5.78 5.26 4.51 5.31 ...
$ wall.motion.index : num 2 1 1 1.41 1 ...
$ class : Factor w/ 2 levels "TRUE","FALSE": 1 1 1 1 1 1 1 1
1 1 ...
and these are the commands:
echoknn.tree <- tree(class ~ ., data=echoknn.train)
predictedClass <- predict(echoknn.tree,echoknn.test)
but predicted classes are
> predictedClass
TRUE FALSE
3 1.000 0.000
5 1.000 0.000
6 1.000 0.000
8 0.875 0.125
10 1.000 0.000
16 1.000 0.000
19 1.000 0.000
26 1.000 0.000
28 1.000 0.000
30 1.000 0.000
39 1.000 0.000
41 1.000 0.000
44 1.000 0.000
59 1.000 0.000
60 1.000 0.000
62 1.000 0.000
65 1.000 0.000
72 0.600 0.400
76 1.000 0.000
79 1.000 0.000
80 1.000 0.000
83 1.000 0.000
96 1.000 0.000
114 0.875 0.125
115 0.875 0.125
117 1.000 0.000
119 0.600 0.400
120 1.000 0.000
122 1.000 0.000
125 1.000 0.000
129 0.875 0.125
131 1.000 0.000
where I go wrong?
Thanks.
Fabio
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