glass: Glass Identification Database

Description Usage Format Source Examples

Description

A data frame with 214 observations, where the problem is to predict the type of glass in terms of their oxide content (i.e. Na, Fe, K, etc). The study of classification of types of glass was motivated by criminological investigation. At the scene of the crime, the glass left can be used as evidence... if it is correctly identified!

Usage

1

Format

A data frame with 214 observations on the following 11 variables.

Id

Id number.

RI

Refractive index.

Na

Sodium (unit measurement: weight percent in corresponding oxide, as are attributes 4-10).

Mg

Magnesium.

Al

Aluminum.

Si

Silicon.

K

Potassium.

Ca

Calcium.

Ba

Barium.

Fe

Iron.

Type

Type of glass: (class attribute)
1 building windows float processed
2 building windows non float processed
3 vehicle windows float processed
4 vehicle windows non float processed (none in this database)
5 containers
6 tableware
7 headlamps

Source

The data have been taken from the UCI Machine Learning Database Repository
http://www.ics.uci.edu/~mlearn/MLRepository.html
and were converted to R format by klaus.schliep@gmail.com.

Examples

1
2

Example output

'data.frame':	214 obs. of  11 variables:
 $ Id  : int  1 2 3 4 5 6 7 8 9 10 ...
 $ RI  : num  1.52 1.52 1.52 1.52 1.52 ...
 $ Na  : num  13.6 13.9 13.5 13.2 13.3 ...
 $ Mg  : num  4.49 3.6 3.55 3.69 3.62 3.61 3.6 3.61 3.58 3.6 ...
 $ Al  : num  1.1 1.36 1.54 1.29 1.24 1.62 1.14 1.05 1.37 1.36 ...
 $ Si  : num  71.8 72.7 73 72.6 73.1 ...
 $ K   : num  0.06 0.48 0.39 0.57 0.55 0.64 0.58 0.57 0.56 0.57 ...
 $ Ca  : num  8.75 7.83 7.78 8.22 8.07 8.07 8.17 8.24 8.3 8.4 ...
 $ Ba  : num  0 0 0 0 0 0 0 0 0 0 ...
 $ Fe  : num  0 0 0 0 0 0.26 0 0 0 0.11 ...
 $ Type: Factor w/ 6 levels "1","2","3","5",..: 1 1 1 1 1 1 1 1 1 1 ...

kknn documentation built on May 2, 2019, 3:26 a.m.