Make Predictions from a "KMeans" Object

Similar to other predict methods, this function predicts fitted values from a fitted "KMeans" object.

# S3 method for KMeans
predict(model, data, key, features = NULL, ...)

Arguments

model

R6Class object
A 'KMeans' object for prediction.
data

DataFrame
DataFrame containting the data.
key

character
Name of the ID column.
features

character of list of characters, optional
Name of feature columns for prediction.
If not provided, it defaults to all non-key columns of data.
...

Reserved parameter.

Format

S3 methods

Value

Predicted values are returned as a DataFrame, structured as follows.

  • ID column: with same name and type as data's ID column.

  • Cluster_ID: type INTEGER, the assigned cluster ID.

  • DISTANCE: type DOUBLE, Distance between a given point and the cluster center.

Examples

Perform the predict on DataFrame data2 using "KMeans" object km:

> data2$Collect()
   ID  V000 V001  V002
1   0   0.5    A   0.5
2   1   1.5    A   0.5
3   2   1.5    A   1.5
4   3   0.5    A   1.5
5   4   1.1    B   1.2
......
19 18  15.5    D   1.5
20 19  15.7    A   1.6

> fitted <- predict(model = km, data = data2, key = "ID")

Output:

> fitted$Collect()
    ID   CLUSTER_ID  DISTANCE
 1   0        0     0.9496364
 2   1        0     0.9224655
 3   2        0     0.8648006
 4   3        0     0.8942320
 5   4        0     0.9787646
 ......
 19 18        3     0.7813475
 20 19        3     1.3365355

See also

hanaml.KMeans