Next: Scaling with Respect to
Up: Experimental Results
Previous: Large Datasets
We also did some experiments to measure the effect of the size of the cache
on the training time.
TABLE 5 shows the results for different
cache sizes, from 10 to 100Mb. In these experiments, we used the first 10000
examples of each dataset (6192 for the smaller Kin) and used
the non-sparse format.
The only clear conclusion from these experiments is that the higher
the size of the cache, the faster SVMTorch is, but the
relation is completely problem dependent.
Table 5:
Training time (in seconds) with respect to the size of the cache
(in Mb).
|
Size of the cache (in Mb) |
|
10 |
20 |
30 |
40 |
50 |
60 |
70 |
80 |
90 |
100 |
Kin |
11 |
11 |
11 |
11 |
11 |
11 |
11 |
11 |
11 |
11 |
Artificial |
359 |
182 |
106 |
100 |
99 |
98 |
98 |
98 |
98 |
98 |
Forest |
869 |
715 |
622 |
519 |
450 |
391 |
355 |
316 |
305 |
272 |
Sunspots |
7 |
7 |
7 |
7 |
7 |
7 |
7 |
7 |
7 |
7 |
MNIST |
729 |
724 |
716 |
704 |
686 |
665 |
647 |
621 |
597 |
573 |
|
Next: Scaling with Respect to
Up: Experimental Results
Previous: Large Datasets
Journal of Machine Learning Research