Results for Exercise Sheet 9 (K-Means clustering)
Please add your row to the table below, following the examples already there. 1. Build time = the time needed to build the sparse term-document matrix from an already built inverted index. Specify in seconds. 2. Clustering time = the total time for the clustering using k-means (without building of the term-document matrix). Specify in minutes and seconds. 3. RSS = the RSS after the last iteration, rounded to the next integer. 4. The number of iterations (each iteration consists of a step A and a step B). 5. Processor / RAM = the specs of the machine you used. Specify the processor frequency with exactly one digit after the dot, the amount of RAM as an integer, and don't provide secondary details about the processor. 6. Language = probably Python.
Name |
Build time |
Clustering time |
Final RSS |
#Iterations |
Processor / RAM |
Language |
Elmar |
4.1s |
0m16s |
317,583 |
20 |
i7-6700 @ 3.4GHz / 64GB |
Python |
Marco |
6.2s |
3m26s |
377,516 |
21 |
i5-4278U @ 2.6GHz / 8GB |
Python |
Robin |
3.7s |
0m38s |
370,808 |
31 |
i7-4510U @ 2.00GHz / 16 GB |
Python |
Daniel |
6.9s |
1m59s |
323,536 |
28 |
Intel Pentium T4500 @ 2.30GHz / 4 GB |
Python |
ES |
6.6s |
2m53s |
301,020 |
39 |
i5-5200U CPU @ 2.20GHz / 8 GB |
Python |
David |
3.9s |
0m48s |
322,971 |
23 |
i5-4670K @ 3.40GHz / 8 GB |
Python |
dumbPy |
6.2s |
6m20s |
317,041 |
50 |
i5 @ 1.7GHz / 2GB Ubuntu VM |
(Init Centr 5min,kmeans 1min) |
Hui Hui |
9.2s |
1m8s |
312,406 |
50 |
Intel Core i5 @ 1.7 GHz - 8GB RAM |
Python |
Elias&Maximilian |
3.3s |
58s |
116,730 |
12 |
i5 @ 2.5 GHz - 4GB RAM |
Python |