BookmarkSubscribeRSS Feed
🔒 This topic is solved and locked. Need further help from the community? Please sign in and ask a new question.
geniusgenie
Obsidian | Level 7

Hi, 

I am using Cutoff node and trying to see Recall score but cannot find it.

I have set the parameter of Cutoff method to Event Precision Equal Recall. In the results I get Overall precision rate and other various values but cannot figure out how would I get recall values and from that value how can I measure f-score/measure.

 

Regards

 

1 ACCEPTED SOLUTION

Accepted Solutions
DougWielenga
SAS Employee

If you go to the SAS Enterprise Miner help available by opening SAS Enterprise Miner and then clicking on Help --> Contents, you can navigate to the Cutoff Node by navigating in the panel on the left to

 

Node Reference

    Assess Nodes

         Cutoff Node

 

and then navigate in the panel on the right to Cutoff Node Train Properties, you can scroll down until you see Event Precision Equal Recall where it says the following: 

    • Event Precision Equal Recall — With precision defined as % true predicted events / (true predicted + false predicted) and recall defined as the event classification rate, this method chooses the point at which precision and recall are equal.

 

There are two ways to find this in the output:  

(1) In the Overall Rates plot, a line is drawn at the requested point and hovering over the line with the mouse will show the cutoff  (see attached document for plot)

(2) In the Output section, you can see the point at which the first two columns are closest is when the cutoff is at 0.36 (I added the bold -- see attached document for partial table).  

 

--------------------------------------------------

|           |            |             |             |Overall |

|           | Event  |  True   | False    |Classif-|

|           |Precisi-|Positive|Positive|ication |

|           |on Rate|  Rate    |  Rate   |   Rate  |

|--------+--------+--------+---------+---------|
|Cutoff |            |            |             |             |
|--------|             |            |             |             |
|0.99    |  200.00|    8.30 |    0.00 |  161.78|

|--------+--------+--------+--------+----------|

|0.98    |  200.00|   13.26|    0.00|  162.77 |

|--------+--------+--------+--------+---------|

|0.97    |  196.67|   15.47|    0.07|  163.15 |

|--------+--------+--------+--------+----------|  

  .            .        .        .        .

  .            .        .        .        .

  .            .        .        .        .

|--------+--------+---------+--------+---------|

|0.38    |  134.11|  125.06|   15.31|  172.80|

|--------+---------+--------+--------+---------|

|0.37    |  132.51|  127.47|   16.18|  172.59|

|--------+---------+--------+--------+---------|

|0.36    |  131.01 | 129.67|  17.01 | 172.36|

|--------+---------+--------+--------+---------|

|0.35    |  128.45|  131.27|   18.22|  171.71|

|--------+---------+--------+--------+---------|

 

I hope this helps!

Doug

View solution in original post

1 REPLY 1
DougWielenga
SAS Employee

If you go to the SAS Enterprise Miner help available by opening SAS Enterprise Miner and then clicking on Help --> Contents, you can navigate to the Cutoff Node by navigating in the panel on the left to

 

Node Reference

    Assess Nodes

         Cutoff Node

 

and then navigate in the panel on the right to Cutoff Node Train Properties, you can scroll down until you see Event Precision Equal Recall where it says the following: 

    • Event Precision Equal Recall — With precision defined as % true predicted events / (true predicted + false predicted) and recall defined as the event classification rate, this method chooses the point at which precision and recall are equal.

 

There are two ways to find this in the output:  

(1) In the Overall Rates plot, a line is drawn at the requested point and hovering over the line with the mouse will show the cutoff  (see attached document for plot)

(2) In the Output section, you can see the point at which the first two columns are closest is when the cutoff is at 0.36 (I added the bold -- see attached document for partial table).  

 

--------------------------------------------------

|           |            |             |             |Overall |

|           | Event  |  True   | False    |Classif-|

|           |Precisi-|Positive|Positive|ication |

|           |on Rate|  Rate    |  Rate   |   Rate  |

|--------+--------+--------+---------+---------|
|Cutoff |            |            |             |             |
|--------|             |            |             |             |
|0.99    |  200.00|    8.30 |    0.00 |  161.78|

|--------+--------+--------+--------+----------|

|0.98    |  200.00|   13.26|    0.00|  162.77 |

|--------+--------+--------+--------+---------|

|0.97    |  196.67|   15.47|    0.07|  163.15 |

|--------+--------+--------+--------+----------|  

  .            .        .        .        .

  .            .        .        .        .

  .            .        .        .        .

|--------+--------+---------+--------+---------|

|0.38    |  134.11|  125.06|   15.31|  172.80|

|--------+---------+--------+--------+---------|

|0.37    |  132.51|  127.47|   16.18|  172.59|

|--------+---------+--------+--------+---------|

|0.36    |  131.01 | 129.67|  17.01 | 172.36|

|--------+---------+--------+--------+---------|

|0.35    |  128.45|  131.27|   18.22|  171.71|

|--------+---------+--------+--------+---------|

 

I hope this helps!

Doug

sas-innovate-2024.png

Join us for SAS Innovate April 16-19 at the Aria in Las Vegas. Bring the team and save big with our group pricing for a limited time only.

Pre-conference courses and tutorials are filling up fast and are always a sellout. Register today to reserve your seat.

 

Register now!

How to choose a machine learning algorithm

Use this tutorial as a handy guide to weigh the pros and cons of these commonly used machine learning algorithms.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 1 reply
  • 4125 views
  • 1 like
  • 2 in conversation