The confusion matrix for the multistage tree applied on the training set objects with at least two harmonics for the first frequency. Each stellar variability class in each node is modelled by a single Gaussian. The last line lists the correct classification (CC) for every class separately. The average correct classification is 92.7 per cent.
| BCEP | DSCUT | CLCEP | DMCEP | MIRA | SR | RRAB | RRC | RRD | SPB | GDOR | ELL | ROT | ACT | ECL | |
| BCEP | 5 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| DSCUT | 1 | 18 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| CLCEP | 0 | 0 | 148 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| DMCEP | 0 | 0 | 0 | 71 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
| MIRA | 0 | 0 | 0 | 0 | 114 | 10 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| SR | 0 | 0 | 0 | 0 | 3 | 55 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 14 |
| RRAB | 0 | 0 | 0 | 2 | 0 | 0 | 67 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| RRC | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 14 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| RRD | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 32 | 0 | 0 | 0 | 0 | 0 | 0 |
| SPB | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 19 | 2 | 1 | 0 | 0 | 0 |
| GDOR | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 7 | 8 | 0 | 0 | 0 | 2 |
| ELL | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 15 | 0 | 0 | 15 |
| ROT | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 23 | 0 | 1 |
| ACT | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 47 | 0 |
| ECL | 0 | 2 | 2 | 0 | 0 | 4 | 0 | 3 | 4 | 3 | 0 | 3 | 3 | 1 | 666 |
| CC | 71.4 | 78.3 | 98.0 | 94.7 | 97.4 | 75.3 | 97.1 | 82.4 | 88.9 | 61.3 | 80.0 | 75.0 | 88.5 | 100.0 | 94.8 |
| BCEP | DSCUT | CLCEP | DMCEP | MIRA | SR | RRAB | RRC | RRD | SPB | GDOR | ELL | ROT | ACT | ECL | |
| BCEP | 5 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| DSCUT | 1 | 18 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| CLCEP | 0 | 0 | 148 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| DMCEP | 0 | 0 | 0 | 71 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
| MIRA | 0 | 0 | 0 | 0 | 114 | 10 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| SR | 0 | 0 | 0 | 0 | 3 | 55 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 14 |
| RRAB | 0 | 0 | 0 | 2 | 0 | 0 | 67 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| RRC | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 14 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| RRD | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 32 | 0 | 0 | 0 | 0 | 0 | 0 |
| SPB | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 19 | 2 | 1 | 0 | 0 | 0 |
| GDOR | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 7 | 8 | 0 | 0 | 0 | 2 |
| ELL | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 15 | 0 | 0 | 15 |
| ROT | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 23 | 0 | 1 |
| ACT | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 47 | 0 |
| ECL | 0 | 2 | 2 | 0 | 0 | 4 | 0 | 3 | 4 | 3 | 0 | 3 | 3 | 1 | 666 |
| CC | 71.4 | 78.3 | 98.0 | 94.7 | 97.4 | 75.3 | 97.1 | 82.4 | 88.9 | 61.3 | 80.0 | 75.0 | 88.5 | 100.0 | 94.8 |
The confusion matrix for the multistage tree applied on the training set objects with at least two harmonics for the first frequency. Each stellar variability class in each node is modelled by a single Gaussian. The last line lists the correct classification (CC) for every class separately. The average correct classification is 92.7 per cent.
| BCEP | DSCUT | CLCEP | DMCEP | MIRA | SR | RRAB | RRC | RRD | SPB | GDOR | ELL | ROT | ACT | ECL | |
| BCEP | 5 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| DSCUT | 1 | 18 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| CLCEP | 0 | 0 | 148 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| DMCEP | 0 | 0 | 0 | 71 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
| MIRA | 0 | 0 | 0 | 0 | 114 | 10 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| SR | 0 | 0 | 0 | 0 | 3 | 55 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 14 |
| RRAB | 0 | 0 | 0 | 2 | 0 | 0 | 67 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| RRC | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 14 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| RRD | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 32 | 0 | 0 | 0 | 0 | 0 | 0 |
| SPB | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 19 | 2 | 1 | 0 | 0 | 0 |
| GDOR | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 7 | 8 | 0 | 0 | 0 | 2 |
| ELL | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 15 | 0 | 0 | 15 |
| ROT | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 23 | 0 | 1 |
| ACT | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 47 | 0 |
| ECL | 0 | 2 | 2 | 0 | 0 | 4 | 0 | 3 | 4 | 3 | 0 | 3 | 3 | 1 | 666 |
| CC | 71.4 | 78.3 | 98.0 | 94.7 | 97.4 | 75.3 | 97.1 | 82.4 | 88.9 | 61.3 | 80.0 | 75.0 | 88.5 | 100.0 | 94.8 |
| BCEP | DSCUT | CLCEP | DMCEP | MIRA | SR | RRAB | RRC | RRD | SPB | GDOR | ELL | ROT | ACT | ECL | |
| BCEP | 5 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| DSCUT | 1 | 18 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| CLCEP | 0 | 0 | 148 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| DMCEP | 0 | 0 | 0 | 71 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
| MIRA | 0 | 0 | 0 | 0 | 114 | 10 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| SR | 0 | 0 | 0 | 0 | 3 | 55 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 14 |
| RRAB | 0 | 0 | 0 | 2 | 0 | 0 | 67 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| RRC | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 14 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| RRD | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 32 | 0 | 0 | 0 | 0 | 0 | 0 |
| SPB | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 19 | 2 | 1 | 0 | 0 | 0 |
| GDOR | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 7 | 8 | 0 | 0 | 0 | 2 |
| ELL | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 15 | 0 | 0 | 15 |
| ROT | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 1 | 0 | 0 | 23 | 0 | 1 |
| ACT | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 47 | 0 |
| ECL | 0 | 2 | 2 | 0 | 0 | 4 | 0 | 3 | 4 | 3 | 0 | 3 | 3 | 1 | 666 |
| CC | 71.4 | 78.3 | 98.0 | 94.7 | 97.4 | 75.3 | 97.1 | 82.4 | 88.9 | 61.3 | 80.0 | 75.0 | 88.5 | 100.0 | 94.8 |
This PDF is available to Subscribers Only
View Article Abstract & Purchase OptionsFor full access to this pdf, sign in to an existing account, or purchase an annual subscription.
