Lite Apriori

Lite Apriori is a R wrapper for SAP HANA PAL LITE_APRIORI.

hanaml.AprioriLite(
  data,
  used.cols = NULL,
  min.support,
  min.confidence,
  thread.ratio = NULL,
  subsample = NULL,
  recalculate = NULL,
  timeout = NULL,
  pmml.export = NULL
)

Arguments

data

DataFrame
DataFrame containting the data.
used.cols

list of characters, optional
Specified the columns in data that specify transaction IDs and item IDs. For example, consider that the transaction ID column for data is "CUSTOMER", while the item ID column for data is "ITEM", then the correct way to set up this parameter is

  • used.cols = list("transaction" = "CUSTOMER", "item" = "ITEM").


Transaction ID column defaults to the 1st column of data, while item ID column defaults to the 2nd column of data.
min.support

numeric
User-specified minimum support value for rule generation.
min.confidence

numeric
User-specified minimum confidence value for rule generation.
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.
subsample

double, optional
User specified subsampling rate of data used for rule mining, ranging from 0 to 1. Set to 1 if you want to used the entire input data.
Defaults to 1.
recalculate

logical, optional
If subsampled, this parameter controls whether or not to use the remaining data to update the computed support, confidence and lift values.
Vaild only when subsample is not 1.
Defaults TRUE.
timeout

integer, optional
Specifies the maximum run time in seconds for association rule mining. The algorithm will stop running when the specified timeout is reached.
Defaults to 3600.
pmml.export

{"no", "single-row", "multi-row"}, optional
Controls whether to output a PMML representation of the model, and how to format the PMML.

  • "no": No PMML model.

  • "single-row": Exports a PMML model in a maximum of one row. Fails if the model doesn't fit in one row.

  • "multi-row": Exports a PMML model, splitting it across multiple rows if it doesn't fit in one.

Default to "no".

Value

An "AprioriLite" object with the following attributes:

  • result: DataFrame
    Mined association rules as a whole. Each rule has its antecedent/consequent items and support/confidence/lift values.

Examples

Input DataFrame data:

> data$Collect()
   CUSTOMER  ITEM
1         2 item2
2         2 item3
3         3 item1
4         3 item2
5         3 item4
6         4 item1
7         4 item3
8         5 item2
9         5 item3
10        6 item1
11        6 item3
12        0 item1
13        0 item2
14        0 item5
15        1 item2
16        1 item4
17        7 item1
18        7 item2
19        7 item3
20        7 item5
21        8 item1
22        8 item2
23        8 item3

Call the function:

> apl <- hanaml.AprioriLite(data = data,
                            used.cols = c("transaction" = "CUSTOMER", "item" = "ITEM"),
                            min.support = 0.1, min.confidence = 0.3,
                            pmml.export = "single-row")

Output:

> apl$result$Collect()
   ANTECEDENT CONSEQUENT   SUPPORT CONFIDENCE      LIFT
1       item5      item2 0.2222222  1.0000000 1.2857143
2       item1      item5 0.2222222  0.3333333 1.5000000
3       item5      item1 0.2222222  1.0000000 1.5000000
4       item5      item3 0.1111111  0.5000000 0.7500000
5       item1      item2 0.4444444  0.6666667 0.8571429
6       item2      item1 0.4444444  0.5714286 0.8571429
7       item4      item2 0.2222222  1.0000000 1.2857143
8       item3      item2 0.4444444  0.6666667 0.8571429
9       item2      item3 0.4444444  0.5714286 0.8571429
10      item4      item1 0.1111111  0.5000000 0.7500000
11      item3      item1 0.4444444  0.6666667 1.0000000
12      item1      item3 0.4444444  0.6666667 1.0000000