5.4.5 - Multi-Threshold Success Table - Teradata Warehouse Miner

Teradata Warehouse Miner User Guide - Volume 3Analytic Functions

Product
Teradata Warehouse Miner
Release Number
5.4.5
Published
February 2018
Language
English (United States)
Last Update
2018-05-04
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This table provides values similar to those in the Prediction Success table, but instead of summing probabilities, the estimated values based on a threshold value are summed instead. Rather than just one threshold however, several thresholds ranging from a user specified low to high value are displayed in user specified increments. This allows the user to compare several success scenarios using different threshold values, to aid in the choice of an ideal threshold.

It might be supposed that the ideal threshold value is the one that maximizes the number of correctly classified observations. However, subjective business considerations may be applied by looking at all of the success values. It may be that wrong predictions in one direction (say estimate 1 when the actual value is 0) may be more tolerable than in the other direction (estimate 0 when the actual value is 1). One may, for example, mind less overlooking fraudulent behavior than wrongly accusing someone of fraud.

The following is an example of a logistic regression multi-threshold success table.

Logistic Regression Multi-Threshold Success table
Threshold Probability Actual Response, Estimate Response Actual Response, Estimate Non-Response Actual Non-Response, Estimate Response Actual Non-Response, Estimate Non-Response
0.0000 375 0 372 0
0.0500 375 0 326 46
0.1000 374 1 231 141
0.1500 372 3 145 227
0.2000 367 8 93 279
0.2500 358 17 59 313
0.3000 354 21 46 326
0.3500 347 28 38 334
0.4000 338 37 32 340
0.4500 326 49 27 345
0.5000 318 57 27 345
0.5500 304 71 26 346
0.6000 296 79 24 348
0.6500 287 88 22 350
0.7000 279 96 21 351
0.7500 270 105 19 353
0.8000 258 117 18 354
0.8500 245 130 16 356
0.9000 222 153 12 360
0.9500 187 188 10 362