PivotalR (version 0.1.18.5)

abalone: Abalone data set

Description

An example data.frame which is used by examples in this user manual

Usage

data(abalone)

Format

Given is the attribute name, attribute type, the measurement unit and a brief description. The number of rings is the value to predict: either as a continuous value or as a classification problem.

Name / Data Type / Measurement Unit / Description

-----------------------------

Id / integer / -- / index of each observation

Sex / nominal / -- / M, F, and I (infant)

Length / continuous / mm / Longest shell measurement

Diameter / continuous / mm / perpendicular to length

Height / continuous / mm / with meat in shell

Whole weight / continuous / grams / whole abalone

Shucked weight / continuous / grams / weight of meat

Viscera weight / continuous / grams / gut weight (after bleeding)

Shell weight / continuous / grams / after being dried

Rings / integer / -- / +1.5 gives the age in years

Details

Predicting the age of abalone from physical measurements. The age of abalone is determined by cutting the shell through the cone, staining it, and counting the number of rings through a microscope -- a boring and time-consuming task. Other measurements, which are easier to obtain, are used to predict the age. Further information, such as weather patterns and location (hence food availability) may be required to solve the problem.

From the original data examples with missing values were removed (the majority having the predicted value missing), and the ranges of the continuous values have been scaled for use with an ANN (by dividing by 200).

Examples

# NOT RUN {
<!-- %% @test .port Database port number -->
<!-- %% @test .dbname Database name -->

## 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 "abalone"
## The user does not need to run data(abalone) to load the data
delete("abalone", conn.id = cid)
x <- as.db.data.frame(abalone, "abalone", key = "id",
                      distributed.by = "id", conn.id = cid,
                      verbose = FALSE)

## preview the actual data
lk(x)

## preview the actual data ordered by id
lk(sort(x, FALSE, x$id))

db.disconnect(cid, verbose = FALSE)
# }