Table 1 Properties of the real-world and synthetic datasets
From: Building efficient fuzzy regression trees for large scale and high dimensional problems
Dataset | F | \(\vert DS \vert\) | \(C_1 (\downarrow )\) | \(C_2 (\downarrow )\) | \(C_4 (\uparrow )\) |
|---|---|---|---|---|---|
Window\(_2\) | 100 | 257,560 | 0.4973 | 0.1103 | 0.9919 |
Window\(_3\) | 140 | 257,560 | 0.4973 | 0.0986 | 0.9918 |
Window\(_4\) | 180 | 257,560 | 0.4973 | 0.0897 | 0.9917 |
Window\(_5\) | 220 | 257,560 | 0.4973 | 0.0805 | 0.9917 |
Window\(_6\) | 260 | 257,560 | 0.4973 | 0.0736 | 0.9917 |
Window\(_7\) | 300 | 257,560 | 0.4973 | 0.0669 | 0.9917 |
Window\(_8\) | 340 | 257,560 | 0.4973 | 0.0613 | 0.9917 |
Window\(_9\) | 380 | 257,560 | 0.4973 | 0.0571 | 0.9917 |
\(f_1\) | 1000 | 100,000 | 0.1614 | 0.0134 | 1.0000 |
\(f_{19}\) | 1000 | 100,000 | 0.0512 | 0.0283 | 1.0000 |
\(f_2\) | 100 | 1,000,000 | 0.0985 | 0.0961 | 1.0000 |
\(f_4\) | 100 | 1,000,000 | 0.0243 | 0.0113 | 1.0000 |