diff options
| author | ziejd2 | 2017-09-28 15:04:40 -0500 |
|---|---|---|
| committer | ziejd2 | 2017-09-28 15:04:40 -0500 |
| commit | 8070dc963753142bb86c4ed698d91fd623ed28e7 (patch) | |
| tree | d0f6dd8fc46a49b819aa55c1a90faa14d8448883 /sourcecodes/bnt-master/SLP/examples/UCI_DataSets/hepatitis.dat | |
| parent | 7cc31810d53176e805532b2789955f4eedbce6bb (diff) | |
| download | BNW-8070dc963753142bb86c4ed698d91fd623ed28e7.tar.gz | |
BNW using Octave instead of Matlab.
This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning. I am calling this BNW_1.02. It can be accessed at: compbio.uthsc.edu/BNW_1.02
Diffstat (limited to 'sourcecodes/bnt-master/SLP/examples/UCI_DataSets/hepatitis.dat')
| -rw-r--r-- | sourcecodes/bnt-master/SLP/examples/UCI_DataSets/hepatitis.dat | 155 |
1 files changed, 155 insertions, 0 deletions
diff --git a/sourcecodes/bnt-master/SLP/examples/UCI_DataSets/hepatitis.dat b/sourcecodes/bnt-master/SLP/examples/UCI_DataSets/hepatitis.dat new file mode 100644 index 00000000..071fabec --- /dev/null +++ b/sourcecodes/bnt-master/SLP/examples/UCI_DataSets/hepatitis.dat @@ -0,0 +1,155 @@ +2 30 2 1 2 2 2 2 1 2 2 2 2 2 1.00 85 18 4.0 -9999 1 +2 50 1 1 2 1 2 2 1 2 2 2 2 2 0.90 135 42 3.5 -9999 1 +2 78 1 2 2 1 2 2 2 2 2 2 2 2 0.70 96 32 4.0 -9999 1 +2 31 1 -9999 1 2 2 2 2 2 2 2 2 2 0.70 46 52 4.0 80 1 +2 34 1 2 2 2 2 2 2 2 2 2 2 2 1.00 -9999 200 4.0 -9999 1 +2 34 1 2 2 2 2 2 2 2 2 2 2 2 0.90 95 28 4.0 75 1 +1 51 1 1 2 1 2 1 2 2 1 1 2 2 -9999 -9999 -9999 -9999 -9999 1 +2 23 1 2 2 2 2 2 2 2 2 2 2 2 1.00 -9999 -9999 -9999 -9999 1 +2 39 1 2 2 1 2 2 2 1 2 2 2 2 0.70 -9999 48 4.4 -9999 1 +2 30 1 2 2 2 2 2 2 2 2 2 2 2 1.00 -9999 120 3.9 -9999 1 +2 39 1 1 1 2 2 2 1 1 2 2 2 2 1.30 78 30 4.4 85 1 +2 32 1 2 1 1 2 2 2 1 2 1 2 2 1.00 59 249 3.7 54 1 +2 41 1 2 1 1 2 2 2 1 2 2 2 2 0.90 81 60 3.9 52 1 +2 30 1 2 2 1 2 2 2 1 2 2 2 2 2.20 57 144 4.9 78 1 +2 47 1 1 1 2 2 2 2 2 2 2 2 2 -9999 -9999 60 -9999 -9999 1 +2 38 1 1 2 1 1 1 2 2 2 2 1 2 2.00 72 89 2.9 46 1 +2 66 1 2 2 1 2 2 2 2 2 2 2 2 1.20 102 53 4.3 -9999 1 +2 40 1 1 2 1 2 2 2 1 2 2 2 2 0.60 62 166 4.0 63 1 +2 38 1 2 2 2 2 2 2 2 2 2 2 2 0.70 53 42 4.1 85 2 +2 38 1 1 1 2 2 2 1 1 2 2 2 2 0.70 70 28 4.2 62 1 +2 22 2 2 1 1 2 2 2 2 2 2 2 2 0.90 48 20 4.2 64 1 +2 27 1 2 2 1 1 1 1 1 1 1 2 2 1.20 133 98 4.1 39 1 +2 31 1 2 2 2 2 2 2 2 2 2 2 2 1.00 85 20 4.0 100 1 +2 42 1 2 2 2 2 2 2 2 2 2 2 2 0.90 60 63 4.7 47 1 +2 25 2 1 1 2 2 2 2 2 2 2 2 2 0.40 45 18 4.3 70 1 +2 27 1 1 2 1 1 2 2 2 2 2 2 2 0.80 95 46 3.8 100 1 +2 49 1 1 1 1 1 1 2 1 2 1 2 2 0.60 85 48 3.7 -9999 1 +2 58 2 2 2 1 2 2 2 1 2 1 2 2 1.40 175 55 2.7 36 1 +2 61 1 1 2 1 2 2 1 1 2 2 2 2 1.30 78 25 3.8 100 1 +2 51 1 1 1 1 1 2 2 2 2 2 2 2 1.00 78 58 4.6 52 1 +1 39 1 1 1 1 1 2 2 1 2 2 2 2 2.30 280 98 3.8 40 1 +1 62 1 1 2 1 1 2 -9999 -9999 2 2 2 2 1.00 -9999 60 -9999 -9999 1 +2 41 2 2 1 1 1 1 2 2 2 2 2 2 0.70 81 53 5.0 74 1 +2 26 2 1 2 2 2 2 2 1 2 2 2 2 0.50 135 29 3.8 60 1 +2 35 1 2 2 1 2 2 2 2 2 2 2 2 0.90 58 92 4.3 73 1 +1 37 1 2 2 1 2 2 2 2 2 1 2 2 0.60 67 28 4.2 -9999 1 +2 23 1 2 2 1 1 1 2 2 1 2 2 2 1.30 194 150 4.1 90 1 +2 20 2 1 2 1 1 1 1 1 1 1 2 2 2.30 150 68 3.9 -9999 1 +2 42 1 1 2 2 2 2 2 2 2 2 2 2 1.00 85 14 4.0 100 1 +2 65 1 2 2 1 1 2 2 1 1 1 1 2 0.30 180 53 2.9 74 2 +2 52 1 1 1 2 2 2 2 2 2 2 2 2 0.70 75 55 4.0 21 1 +2 23 1 2 2 2 2 2 -9999 -9999 -9999 -9999 -9999 -9999 4.60 56 16 4.6 -9999 1 +2 33 1 2 2 2 2 2 2 2 2 2 2 2 1.00 46 90 4.4 60 1 +2 56 1 1 2 1 2 2 2 2 2 2 2 2 0.70 71 18 4.4 100 1 +2 34 1 2 2 2 2 2 2 2 2 2 2 2 -9999 -9999 86 -9999 -9999 1 +2 28 1 2 2 1 1 2 2 2 2 2 2 2 0.70 74 110 4.4 -9999 1 +2 37 1 1 2 2 2 2 2 1 2 1 2 2 0.60 80 80 3.8 -9999 1 +2 28 2 2 2 1 1 2 2 1 2 2 2 2 1.80 191 420 3.3 46 1 +2 36 1 1 2 2 2 2 2 2 1 2 2 2 0.80 85 44 4.2 85 1 +2 38 1 2 1 1 1 1 2 2 2 1 2 2 0.70 125 65 4.2 77 1 +2 39 1 1 2 2 2 2 2 2 2 2 2 2 0.90 85 60 4.0 -9999 1 +2 39 1 2 2 2 2 2 2 2 2 2 2 2 1.00 85 20 4.0 -9999 1 +2 44 1 2 2 2 2 2 2 2 2 2 2 2 0.60 110 145 4.4 70 1 +2 40 1 2 1 1 2 2 2 1 1 2 2 2 1.20 85 31 4.0 100 1 +2 30 1 2 2 1 2 2 2 2 2 2 2 2 0.70 50 78 4.2 74 1 +2 37 1 1 2 1 1 1 2 2 2 2 2 2 0.80 92 59 -9999 -9999 1 +2 34 1 1 2 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 1 +2 30 1 2 1 2 2 2 2 2 2 2 2 2 0.70 52 38 3.9 52 1 +2 64 1 2 1 1 1 2 1 1 2 2 2 2 1.00 80 38 4.3 74 1 +2 45 2 1 2 1 1 2 2 2 1 2 2 2 1.00 85 75 -9999 -9999 1 +2 37 1 2 2 2 2 2 2 2 2 2 2 2 0.70 26 58 4.5 100 1 +2 32 1 2 2 2 2 2 2 2 2 2 2 2 0.70 102 64 4.0 90 1 +2 32 1 2 2 1 1 1 2 2 2 1 2 1 3.50 215 54 3.4 29 1 +2 36 1 1 2 2 2 2 1 1 1 2 2 2 0.70 164 44 3.1 41 1 +2 49 1 2 2 1 1 2 2 2 2 2 2 2 0.80 103 43 3.5 66 1 +2 27 1 2 2 2 2 2 2 2 2 2 2 2 0.80 -9999 38 4.2 -9999 1 +2 56 1 1 2 2 2 2 2 2 2 2 2 2 0.70 62 33 3.0 -9999 1 +1 57 1 2 2 1 1 1 2 2 2 1 1 2 4.10 -9999 48 2.6 73 1 +2 39 1 2 2 1 2 2 2 2 2 2 2 2 1.00 34 15 4.0 54 1 +2 44 1 1 2 1 1 2 2 2 2 2 2 2 1.60 68 68 3.7 -9999 1 +2 24 1 2 2 2 2 2 2 2 2 2 2 2 0.80 82 39 4.3 -9999 1 +1 34 1 1 2 1 1 2 1 1 2 1 2 2 2.80 127 182 -9999 -9999 1 +2 51 1 2 2 1 1 1 -9999 -9999 -9999 -9999 -9999 -9999 0.90 76 271 4.4 -9999 1 +2 36 1 1 2 1 1 1 2 1 2 2 2 2 1.00 -9999 45 4.0 57 1 +2 50 1 2 2 2 2 2 2 2 2 2 2 2 1.50 100 100 5.3 -9999 1 +2 32 1 1 1 1 1 2 2 2 2 2 2 2 1.00 55 45 4.1 56 1 +1 58 1 2 2 1 2 2 1 1 1 1 2 2 2.00 167 242 3.3 -9999 1 +2 34 2 1 1 2 2 2 2 1 2 2 2 2 0.60 30 24 4.0 76 1 +2 34 1 1 2 1 2 2 1 1 2 1 2 2 1.00 72 46 4.4 57 1 +2 28 1 2 2 2 2 2 2 2 2 2 2 2 0.70 85 31 4.9 -9999 1 +2 23 1 2 2 1 1 1 2 2 2 2 2 2 0.80 -9999 14 4.8 -9999 1 +2 36 1 2 2 2 2 2 2 2 2 2 2 2 0.70 62 224 4.2 100 1 +2 30 1 1 2 2 2 2 2 2 2 2 2 2 0.70 100 31 4.0 100 1 +2 67 2 1 2 1 1 2 2 2 -9999 -9999 -9999 -9999 1.50 179 69 2.9 -9999 1 +2 62 2 2 2 1 1 2 2 1 2 1 2 2 1.30 141 156 3.9 58 1 +2 28 1 1 2 1 1 1 2 1 2 2 2 2 1.60 44 123 4.0 46 1 +1 44 1 1 2 1 1 2 2 2 1 2 2 1 0.90 135 55 -9999 41 2 +1 30 1 2 2 1 1 1 2 1 2 1 1 1 2.50 165 64 2.8 -9999 2 +1 38 1 1 2 1 1 1 2 1 2 1 1 1 1.20 118 16 2.8 -9999 2 +2 38 1 1 2 1 1 1 1 1 2 2 2 2 0.60 76 18 4.4 84 2 +2 50 2 1 2 1 2 2 1 1 1 1 2 2 0.90 230 117 3.4 41 2 +1 42 1 1 2 1 1 1 2 2 1 1 2 1 4.60 -9999 55 3.3 -9999 2 +2 33 1 2 2 2 2 2 -9999 -9999 2 2 2 2 1.00 -9999 60 4.0 -9999 2 +2 52 1 1 2 2 2 2 2 2 2 2 2 2 1.50 -9999 69 2.9 -9999 2 +1 59 1 1 2 1 1 2 2 1 1 1 2 2 1.50 107 157 3.6 38 2 +2 40 1 1 1 1 1 1 1 1 2 2 2 2 0.60 40 69 4.2 67 2 +2 30 1 1 2 1 1 2 2 1 2 1 2 2 0.80 147 128 3.9 100 2 +2 44 1 1 2 1 1 2 1 1 2 1 2 2 3.00 114 65 3.5 -9999 2 +1 47 1 2 2 2 2 2 2 2 2 1 2 1 2.00 84 23 4.2 66 2 +2 60 1 1 2 1 2 2 1 1 1 1 2 2 -9999 -9999 40 -9999 -9999 2 +1 48 1 1 2 1 1 2 2 1 2 1 1 1 4.80 123 157 2.7 31 2 +2 22 1 2 2 2 2 2 2 2 2 2 2 2 0.70 -9999 24 -9999 -9999 2 +2 27 1 1 2 1 2 2 2 1 2 2 2 2 2.40 168 227 3.0 66 2 +2 51 1 1 2 1 1 1 2 1 1 1 2 1 4.60 215 269 3.9 51 2 +1 47 1 2 2 1 1 2 2 1 2 2 1 1 1.70 86 20 2.1 46 2 +2 25 1 2 2 2 2 2 2 2 2 2 2 2 0.60 -9999 34 6.4 -9999 2 +1 35 1 1 2 1 2 2 -9999 -9999 1 1 1 2 1.50 138 58 2.6 -9999 2 +2 45 1 1 2 1 1 1 2 2 2 2 2 2 2.30 -9999 648 -9999 -9999 2 +2 54 1 1 1 2 2 2 1 1 2 2 2 2 1.00 155 225 3.6 67 2 +1 33 1 1 2 1 1 2 2 2 2 2 1 2 0.70 63 80 3.0 31 2 +2 7 1 2 2 2 2 2 2 1 1 2 2 2 0.70 256 25 4.2 -9999 2 +1 42 1 1 1 1 1 2 2 2 2 1 2 2 0.50 62 68 3.8 29 2 +2 52 1 1 2 1 2 2 2 2 2 2 2 2 1.00 85 30 4.0 -9999 2 +2 45 1 1 2 1 2 2 2 1 1 2 2 2 1.20 81 65 3.0 -9999 1 +2 36 1 1 2 2 2 2 2 2 2 2 2 2 1.10 141 75 3.3 -9999 2 +2 69 2 2 2 1 2 2 2 2 2 2 2 2 3.20 119 136 -9999 -9999 2 +2 24 1 1 2 1 2 2 2 2 2 2 2 2 1.00 -9999 34 4.1 -9999 2 +2 50 1 2 2 2 2 2 2 2 2 2 2 2 1.00 139 81 3.9 62 2 +1 61 1 1 2 1 1 2 -9999 -9999 2 1 2 2 -9999 -9999 -9999 -9999 -9999 2 +2 54 1 2 2 1 2 2 1 1 2 2 2 2 3.20 85 28 3.8 -9999 2 +1 56 1 1 2 1 1 1 1 1 2 1 2 2 2.90 90 153 4.0 -9999 2 +2 20 1 1 2 1 1 1 2 2 2 1 1 2 1.00 160 118 2.9 23 2 +2 42 1 2 2 2 2 2 2 2 1 2 2 2 1.50 85 40 -9999 -9999 2 +2 37 1 1 2 1 2 2 2 2 2 1 2 2 0.90 -9999 231 4.3 -9999 2 +2 50 1 2 2 2 2 2 2 1 1 1 2 2 1.00 85 75 4.0 72 2 +2 34 2 2 2 1 1 1 1 1 2 1 2 2 0.70 70 24 4.1 100 2 +2 28 1 2 2 1 1 1 -9999 -9999 2 1 1 2 1.00 -9999 20 4.0 -9999 2 +1 50 1 2 2 1 2 2 2 1 1 2 1 1 2.80 155 75 2.4 32 2 +2 54 1 1 2 1 1 2 2 2 2 2 1 2 1.20 85 92 3.1 66 2 +1 57 1 1 2 1 1 2 2 2 2 1 1 2 4.60 82 55 3.3 30 2 +2 54 1 2 2 2 2 2 2 2 2 2 2 2 1.00 85 30 4.5 0 2 +1 31 1 1 2 1 1 1 2 2 1 2 2 2 8.00 -9999 101 2.2 -9999 2 +2 48 1 2 2 1 1 1 2 1 2 1 2 2 2.00 158 278 3.8 -9999 2 +2 72 1 2 1 1 2 2 2 1 2 2 2 2 1.00 115 52 3.4 50 2 +1 38 1 1 2 2 2 2 2 1 2 2 2 2 0.40 243 49 3.8 90 2 +2 25 1 2 2 1 2 2 1 1 1 1 1 1 1.30 181 181 4.5 57 2 +2 51 1 2 2 2 2 2 1 1 2 1 2 2 0.80 -9999 33 4.5 -9999 2 +2 38 1 2 2 2 2 2 2 1 2 1 2 1 1.60 130 140 3.5 56 2 +1 47 1 2 2 1 1 2 2 1 2 1 1 1 1.00 166 30 2.6 31 2 +2 45 1 2 1 2 2 2 2 2 2 2 2 2 1.30 85 44 4.2 85 2 +2 36 1 1 2 1 1 1 1 1 2 1 2 1 1.70 295 60 2.7 -9999 2 +1 54 1 1 2 1 1 2 -9999 -9999 1 2 1 2 3.90 120 28 3.5 43 2 +2 51 1 2 2 1 2 2 2 1 1 1 2 1 1.00 -9999 20 3.0 63 2 +1 49 1 1 2 1 1 2 2 2 1 1 2 2 1.40 85 70 3.5 35 2 +1 45 1 2 2 1 1 1 2 2 2 1 1 2 1.90 -9999 114 2.4 -9999 2 +2 31 1 1 2 1 2 2 2 2 2 2 2 2 1.20 75 173 4.2 54 2 +1 41 1 2 2 1 2 2 2 1 1 1 2 1 4.20 65 120 3.4 -9999 2 +1 70 1 1 2 1 1 1 -9999 -9999 -9999 -9999 -9999 -9999 1.70 109 528 2.8 35 2 +2 20 1 1 2 2 2 2 2 -9999 2 2 2 2 0.90 89 152 4.0 -9999 2 +2 36 1 2 2 2 2 2 2 2 2 2 2 2 0.60 120 30 4.0 -9999 2 +1 46 1 2 2 1 1 1 2 2 2 1 1 1 7.60 -9999 242 3.3 50 2 +2 44 1 2 2 1 2 2 2 1 2 2 2 2 0.90 126 142 4.3 -9999 2 +2 61 1 1 2 1 1 2 1 1 2 1 2 2 0.80 75 20 4.1 -9999 2 +2 53 2 1 2 1 2 2 2 2 1 1 2 1 1.50 81 19 4.1 48 2 +1 43 1 2 2 1 2 2 2 2 1 1 1 2 1.20 100 19 3.1 42 2 |