Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/15746#discussion_r86657586
--- Diff: R/pkg/R/mllib.R ---
@@ -1828,13 +1849,13 @@ setMethod("summary", signature(object =
"RandomForestRegressionModel"),
#' @note summary(RandomForestClassificationModel) since 2.1.0
setMethod("summary", signature(object = "RandomForestClassificationModel"),
function(object) {
- ans <- summary.randomForest(object)
+ ans <- summary.treeEnsemble(object)
class(ans) <- "summary.RandomForestClassificationModel"
ans
})
# Prints the summary of Random Forest Regression Model
-print.summary.randomForest <- function(x) {
+print.summary.treeEnsemble <- function(x) {
--- End diff --
For example, summary on `rpart` model shows both error and node-by-node
information. I think it is still useful this way
```
Call:
rpart(formula = Kyphosis ~ Age + Number + Start, data = kyphosis,
method = "class")
n= 81
CP nsplit rel error xerror xstd
1 0.17647059 0 1.0000000 1.0000000 0.2155872
2 0.01960784 1 0.8235294 0.9411765 0.2107780
3 0.01000000 4 0.7647059 1.0588235 0.2200975
Variable importance
Start Age Number
64 24 12
Node number 1: 81 observations, complexity param=0.1764706
predicted class=absent expected loss=0.2098765 P(node) =1
class counts: 64 17
probabilities: 0.790 0.210
left son=2 (62 obs) right son=3 (19 obs)
Primary splits:
Start < 8.5 to the right, improve=6.762330, (0 missing)
Number < 5.5 to the left, improve=2.866795, (0 missing)
Age < 39.5 to the left, improve=2.250212, (0 missing)
Surrogate splits:
Number < 6.5 to the left, agree=0.802, adj=0.158, (0 split)
Node number 2: 62 observations, complexity param=0.01960784
predicted class=absent expected loss=0.09677419 P(node) =0.7654321
class counts: 56 6
probabilities: 0.903 0.097
left son=4 (29 obs) right son=5 (33 obs)
Primary splits:
Start < 14.5 to the right, improve=1.0205280, (0 missing)
Age < 55 to the left, improve=0.6848635, (0 missing)
Number < 4.5 to the left, improve=0.2975332, (0 missing)
Surrogate splits:
Number < 3.5 to the left, agree=0.645, adj=0.241, (0 split)
Age < 16 to the left, agree=0.597, adj=0.138, (0 split)
Node number 3: 19 observations
predicted class=present expected loss=0.4210526 P(node) =0.2345679
class counts: 8 11
probabilities: 0.421 0.579
Node number 4: 29 observations
predicted class=absent expected loss=0 P(node) =0.3580247
class counts: 29 0
probabilities: 1.000 0.000
Node number 5: 33 observations, complexity param=0.01960784
predicted class=absent expected loss=0.1818182 P(node) =0.4074074
class counts: 27 6
probabilities: 0.818 0.182
left son=10 (12 obs) right son=11 (21 obs)
Primary splits:
Age < 55 to the left, improve=1.2467530, (0 missing)
Start < 12.5 to the right, improve=0.2887701, (0 missing)
Number < 3.5 to the right, improve=0.1753247, (0 missing)
Surrogate splits:
Start < 9.5 to the left, agree=0.758, adj=0.333, (0 split)
Number < 5.5 to the right, agree=0.697, adj=0.167, (0 split)
Node number 10: 12 observations
predicted class=absent expected loss=0 P(node) =0.1481481
class counts: 12 0
probabilities: 1.000 0.000
Node number 11: 21 observations, complexity param=0.01960784
predicted class=absent expected loss=0.2857143 P(node) =0.2592593
class counts: 15 6
probabilities: 0.714 0.286
left son=22 (14 obs) right son=23 (7 obs)
Primary splits:
Age < 111 to the right, improve=1.71428600, (0 missing)
Start < 12.5 to the right, improve=0.79365080, (0 missing)
Number < 3.5 to the right, improve=0.07142857, (0 missing)
Node number 22: 14 observations
predicted class=absent expected loss=0.1428571 P(node) =0.1728395
class counts: 12 2
probabilities: 0.857 0.143
Node number 23: 7 observations
predicted class=present expected loss=0.4285714 P(node) =0.08641975
class counts: 3 4
probabilities: 0.429 0.571
```
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