1402
Comment: speed result with just one figure after decimal
|
1487
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Deletions are marked like this. | Additions are marked like this. |
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||Florian B ||6.5s ||16.0s ||9.5s ||30% || Intel X5560 @ 2.8GHz / 36GB ||Java || || ||Florian B ||7.8s ||12.6s ||2.1s ||55% || Intel X5560 @ 2.8GHz / 36GB ||Java ||no stopwords + only frequent words || |
||Florian B ||6.5s ||16.0s ||9.5s ||27% || Intel X5560 @ 2.8GHz / 36GB ||Java || || ||Florian B ||7.8s ||12.6s ||2.1s ||41% || Intel X5560 @ 2.8GHz / 36GB ||Java ||no stopwords + top 15 words per doc || |
Line 12: | Line 12: |
||Matthias H. ||10.0s ||0.1s ||43.0s ||47% || Intel i5 @ 1.7GHz / 4GB ||Java || || |
Results for Exercise Sheet 10 (Naive Bayes)
Please read the instructions below, before adding something to the table!
Add your row to the table below, following the examples already there. Column 2, 3, and 4 = running time of your program for reading the CSV file, training, and prediction, respectively, in seconds (with exactly one digit after the dot). Column 5 = percentage of your predictions that were correct. Column 5 = machine specification as usual (processor frequency with exactly one digit after the dot, amount of RAM as an integer, no secondary details about processor). Column 6 = programming language (Java or C++). Column 7 = A short description of the feature selection improvements you made (if you made any).
Name |
Reading time |
Training time |
Prediction time |
Correct % |
Processor / RAM |
Language |
Feature Selection |
Florian B |
6.5s |
16.0s |
9.5s |
27% |
Intel X5560 @ 2.8GHz / 36GB |
Java |
|
Florian B |
7.8s |
12.6s |
2.1s |
41% |
Intel X5560 @ 2.8GHz / 36GB |
Java |
no stopwords + top 15 words per doc |
Christoph S |
15.5s |
0.4s |
0.7s |
53% |
Core 2 Quad @ 2.8GHz / 4GB |
C++ |
|
Christoph S |
36.6s |
1.1s |
4.9s |
62% |
Core 2 Duo @ 1.6GHz / 2GB |
C++ |
no stopwords |
Matthias H. |
24.8s |
0.4s |
1.7s |
42% |
Intel i3 @ 1.3GHz / 4GB |
Java |
|
Matthias H. |
10.0s |
0.1s |
43.0s |
47% |
Intel i5 @ 1.7GHz / 4GB |
Java |
|