groups {PivotalR} | R Documentation |
The function prints the value of each element in the Logistic Regression output object.
## S3 method for class 'lm.madlib' groups(x) ## S3 method for class 'lm.madlib.grps' groups(x) ## S3 method for class 'logregr.madlib' groups(x) ## S3 method for class 'logregr.madlib.grps' groups(x)
x |
The result of |
A list that contains the value of each grouping colum. The elements
of the list are the same as the grouping columns. If x
is a
lm.madlib
object with one group's information in it, the
elements of the resulting list contain one value for each grouping
column. If x
is lm.madlib.grps
, which contains
multiple groups' information, then each element of the resulting
list is a vector with the length equal to the number of different
groups. logregr.madlib
and logregr.madlib.grps
have
the similar interpretation of the results.
If no grouping column is used, this funcion returns NULL
.
Author: Predictive Analytics Team at Pivotal Inc.
Maintainer: Frank McQuillan, Pivotal Inc. fmcquillan@pivotal.io
madlib.glm
wrapper for MADlib linear and logistic regressions.
madlib.lm
wrapper for MADlib linear regression
predict.lm.madlib
, predict.lm.madlib.grps
,
predict.logregr.madlib
,
predict.logregr.madlib.grps
make
predictions for new data.
## 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) ## create a table from the example data.frame delete("abalone", conn.id = cid) source_data <- as.db.data.frame(abalone, "abalone", conn.id = cid, verbose = FALSE) lk(source_data, 10) ## logistic regression fit <- madlib.glm(rings < 10 ~ . - id | sex , data = source_data, family = "binomial") groups(fit) # all grouping column values groups(fit[[1]]) # the first model's grouping column value db.disconnect(cid, verbose = FALSE) ## End(Not run)