Timeline for How to binary encode multi-valued categorical variable from Pandas dataframe?
Current License: CC BY-SA 4.0
11 events
| when toggle format | what | by | license | comment | |
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| S Aug 1, 2020 at 15:44 | history | suggested | Zephyr | CC BY-SA 4.0 |
Corrected link quote
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| Aug 1, 2020 at 14:25 | review | Suggested edits | |||
| S Aug 1, 2020 at 15:44 | |||||
| Oct 5, 2015 at 12:37 | vote | accept | Denis L | ||
| Oct 1, 2015 at 12:19 | history | edited | Samuel Harrold | CC BY-SA 3.0 |
Used pandas broadcasting rather than a for loop.
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| Oct 1, 2015 at 11:41 | comment | added | Samuel Harrold | Both pandas and scipy have sparse data structures (pandas sparse, scipy sparse) for saving memory, but they might not be supported by the machine learning library you use. If the dimensionality of your problem (number of columns) is so large that sparse representation is necessary, you may want to consider also using dimensionality reduction techniques. | |
| Oct 1, 2015 at 10:58 | comment | added | Denis L | Thanks, I'll check it out. Actually, the 0, 1, and 2 are the index. Also, do you have any idea how sparseness can be handled efficiently here as there are lots of zeroes? | |
| Sep 30, 2015 at 22:25 | history | edited | Samuel Harrold | CC BY-SA 3.0 |
Fixed grammar for "index". Added "In/Out" labels for pre-formatted cells.
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| Sep 30, 2015 at 19:22 | history | edited | Samuel Harrold | CC BY-SA 3.0 |
added 534 characters in body
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| Sep 30, 2015 at 18:36 | history | edited | Samuel Harrold | CC BY-SA 3.0 |
added 5 characters in body
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| Sep 30, 2015 at 18:31 | review | First posts | |||
| Sep 30, 2015 at 23:17 | |||||
| Sep 30, 2015 at 18:31 | history | answered | Samuel Harrold | CC BY-SA 3.0 |