Description Usage Arguments Value Author(s) References See Also Examples
This function is a wrapper of MADlib's random forest model get_tree
function. The model built using madlib.randomForest
is passed
as input to this function.
1 | getTree.rf.madlib(object, k=1, ...)
|
object |
A random forest model object built using |
k |
Id of the tree to be retrieved. Can range between 1 and maximum number of trees in the forest. default is 1. |
... |
Arguments to be passed to or from other methods. |
A data frame object similar to R's getTree result.
Author: Predictive Analytics Team at Pivotal Inc.
Maintainer: Frank McQuillan, Pivotal Inc. fmcquillan@pivotal.io
[1] Documentation of random forest in MADlib 1.7, https://madlib.apache.org/docs/latest/
madlib.randomForest
function to train a random forest model.
print.rf.madlib
function to print summary of a model fitted
through madlib.randomForest
predict.rf.madlib
is a wrapper for MADlib's predict function for
random forests.
madlib.lm
, madlib.glm
,
madlib.summary
, madlib.arima
, madlib.elnet
,
madlib.rpart
are all MADlib wrapper functions.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | ## Not run:
## set up the database connection
## Assume that .port is port number and .dbname is the database name
cid <- db.connect(port = .port, dbname = .dbname, verbose = FALSE)
x <- as.db.data.frame(abalone, conn.id = cid, verbose = FALSE)
lk(x, 10)
## decision tree using abalone data, using default values of minsplit,
## maxdepth etc.
key(x) <- "id"
fit <- madlib.randomForest(rings < 10 ~ length + diameter + height + whole + shell,
data=x)
fit
getTree.rf.madlib(fit, k=2)
db.disconnect(cid)
## End(Not run)
|
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