Affinity Propagation

hanaml.AffinityPropagation is a R wrapper for SAP HANA PAL Affinity Propagation algorithm.

hanaml.AffinityPropagation(
  data,
  key,
  features = NULL,
  affinity,
  n.clusters,
  max.iter = NULL,
  convergence.iter = NULL,
  damping = NULL,
  preference = NULL,
  seed.ratio = NULL,
  times = NULL,
  minkowski.power = NULL,
  thread.ratio = NULL
)

Arguments

data	DataFrame DataFrame containting the data.
key	character Name of the ID column.
features	character or list of characters, optional Names of features columns. If is not provided, it defaults to all non-key columns of data.
affinity	character Ways to compute the distance between two points. 'manhattan' 'euclidean' 'minkowski' 'chebyshev' 'standardized.euclidean' 'cosine' No default value as it is mandatory.
n.clusters	integer 0: Does not adjust Affinity Propagation cluster result. Non-zero integer: If Affinity Propagation cluster number is bigger than n.clusters, PAL will merge the result to make the cluster number be the value specified for n.clusters.
max.iter	integer, optional Maximum number of iterations. Defaults to 500.
convergence.iter	integer, optional When the clusters keep a steady one for the specified times, the algorithm ends. Defaults to 100.
damping	double, optional Controls the updating velocity. Value range: (0, 1). Defaults to 0.9.
preference	double, optional Determines the preference. Value range: [0,1]. Defaults to 0.5.
seed.ratio	double, optional Select a portion of (seed.ratio * data_number) the input data as seed, where data_number is the row-size of the input data. Value range: (0,1]. If seed.ratio is 1, all the input data will be the seed. Defaults to 1.
times	integer, optional The sampling times. Only valid when seed.ratio is less than 1 and affinity is 'minkowski'. Defaults to 3.
minkowski.power	integer, optional The sampling times. Only valid when affinity is 'minkowski'. Defaults to 1.
thread.ratio	double, optional Controls the proportion of available threads that can be used by this function. The value range is from 0 to 1, where 0 indicates a single thread, and 1 indicates all available threads. Values between 0 and 1 will use up to that percentage of available threads.Values outside this range are ignored. Defaults to 0.

Value

An "AffinityPropagation" object with the following attributes:

• labels : DataFrame
  Label assigned to each sample,structured as follows:

  • ID record ID.
    

  • CLUSTER_ID the range is from 0 to n.clusters - 1.

• statistics : DataFrame
  Statistic value, structured as follows:

  • STAT_NAME Statistic name.

  • STAT_VALUE Statistic value.

Examples

Input DataFrame data:

> data$Collect()
    ID     V1     V2
1    1   0.10   0.10
2    2   0.11   0.10
3    3   0.10   0.11
4    4   0.11   0.11
5    5   0.12   0.11
6    6   0.11   0.12
21  21  10.13  10.12
22  22  10.13  10.13
23  23  10.13  10.14
24  24  10.14  10.13

Call the function:

> ap <- hanaml.AffinityPropagation(data = data,
                                   key = "ID",
                                   affinity = "euclidean",
                                   n.clusters = 0L,
                                   max.iter = 500L,
                                   convergence.iter = 100L,
                                   damping = 0.9,
                                   preference = 0.5,
                                   times = 1L,
                                   seed.ratio = 1,
                                   minkowski.power = 0,
                                   thread.ratio = 0)

Output:

> ap$labels$collect()
    ID  CLUSTER_ID
1    1           0
2    2           0
3    3           0
4    4           0
5    5           0
6    6           0
......
22  22           1
23  23           1
24  24           1