Timeline for Convert categorical data in numeric preserve euclidean distance
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jan 2, 2022 at 15:10 | comment | added | Malo | Using 10 and 20 may be not good as you need to scale or standardize your values before calculating a distance metric. So evey value is betwwen 0 and 1 or -1 and 1 | |
| Jan 2, 2022 at 15:09 | comment | added | Malo | It is 0 or 1 if you have OneHotEncoded the categorical feature. Before encoding a categorcial value can be : red, bue, white, yellow if you consider a color.... | |
| Mar 27, 2019 at 7:49 | comment | added | theantomc | i wish avoid that people will be cluster as the same , for value that i had put in my dataset | |
| Mar 26, 2019 at 22:01 | comment | added | William Scott | Yes. then in that case, the value defined will just make sure that the intra cluster distance is more. But even if the values are binary, the clusters will be same. | |
| Mar 26, 2019 at 9:01 | comment | added | theantomc | But if i have 2 attribute, ad example M and F and another features that represent subscribe or not in a website ad example (that can i have just value like yes and no) I have M= 1, F=0 and Yes=1 , No=0 ...So male guys that are subscribe will be cluster togheter...this make sense? | |
| Mar 26, 2019 at 6:41 | history | answered | William Scott | CC BY-SA 4.0 |