| Column Name | Data Type | Description |
|---|---|---|
| partition_column | ANY | Column to copy to output table. Used to partition input data and output table. |
| TD_item1 | VARCHAR | Name of item1. |
| TD_item2 | VARCHAR | Name of item2. |
| cntb | INTEGER | Count of co-occurrence of both items in partition. |
| cnt1 | INTEGER | Count of occurrence of item1 in partition. |
| cnt2 | INTEGER | Count of occurrence of item2 in partition. |
| score | REAL | Product of two conditional probabilities: P({ item2 | item1 }) * P({ item1 | item2 }) Preceding product equals following quotient: (cntb * cntb)/(cnt1 * cnt2) |
| support | REAL | Percentage of transactions in partition in which the two items co-occur, calculated with this formula: cntb/tran_cnt where tran_cnt is the number of transactions in the partition. |
| confidence | REAL | Percentage of transactions in partition in which item1 occurs, in which item2 also occurs, calculated with this formula: cntb/cnt1 |
| lift | REAL | Ratio of observed support value to expected support value if item1 and item2 were independent; that is: support(item1 and item2) / [support(item1) * support(item2)] Value is calculated with this formula: (cntb/tran_cnt) / [(cnt1/tran_cnt) * (cnt2/tran_cnt)] If lift > 1, the occurrence of item1 or item2 has a positive effect on the occurrence of the other items. If lift = 1, the occurrence of item1 or item2 has a no effect on the occurrence of the other items. If lift < 1, the occurrence of item1 or item2 has a negative effect on the occurrence of the other items. |
| z_score | REAL | Significance of co-occurrence, assuming that cntb follows a normal distribution, calculated with this formula: (cntb - mean(cntb)) / sd(cntb) If all cntb values are equal, then sd(cntb) is 0, and function does not calculate zscore. |