Input
The input table, computers_category, has five attributes of personal computers—price, speed, hard disk size, RAM, and screen size. The table has 500 rows, categorized into five price groups—SPECIAL, SUPER, HYPER, MEGA and UBER. The predicted_compcategory values can be output by a classification function, such as KNN.
| compid | price | speed | hd | ram | screen | expected_compcategory | predicted_compcategory |
|---|---|---|---|---|---|---|---|
| 1 | 1499 | 25 | 80 | 4 | 14 | SPECIAL | SPECIAL |
| 2 | 1795 | 33 | 85 | 2 | 14 | SUPER | SUPER |
| 3 | 1595 | 25 | 170 | 4 | 15 | SPECIAL | SPECIAL |
| 4 | 1849 | 25 | 170 | 8 | 14 | SUPER | HYPER |
| 5 | 3295 | 33 | 340 | 16 | 14 | HYPER | SUPER |
| 6 | 3695 | 66 | 340 | 16 | 14 | UBER | SPECIAL |
| 7 | 1720 | 25 | 170 | 4 | 14 | SPECIAL | SPECIAL |
| 8 | 1995 | 50 | 85 | 2 | 14 | SUPER | SUPER |
| 9 | 2225 | 50 | 210 | 8 | 14 | SUPER | SUPER |
| 12 | 2605 | 66 | 210 | 8 | 14 | MEGA | UBER |
| 13 | 2045 | 50 | 130 | 4 | 14 | SUPER | SUPER |
| 14 | 2295 | 25 | 245 | 8 | 14 | MEGA | MEGA |
| 16 | 2225 | 50 | 130 | 4 | 14 | SUPER | SUPER |
| ... | ... | ... | ... | ... | ... | ... | ... |
SQL Call
SELECT * FROM FMeasure (
ON computers_category PARTITION BY 1
USING
ObsColumn ('expected_compcategory')
PredictColumn ('predicted_compcategory')
Beta (1.0)
) AS dt;
Output
| class | precision | recall | beta | fmeasure |
|---|---|---|---|---|
| HYPER | 0.936842105263158 | 0.89 | 1 | 0.912820512820513 |
| MEGA | 0.923076923076923 | 0.935064935064935 | 1 | 0.929032258064516 |
| SPECIAL | 0.84375 | 0.885245901639344 | 1 | 0.864 |
| SUPER | 0.935897435897436 | 0.954248366013072 | 1 | 0.944983818770227 |
| UBER | 0.896551724137931 | 0.8125 | 1 | 0.852459016393443 |
| -AVG- | 0.918 | 0.918 | 1 | 0.918 |