如何分析 Weka 中的混淆矩阵以获得准确度?我们知道,由于数据集不平衡,准确性并不准确。混淆矩阵如何“确认”准确性?
示例: a) 准确度 96.1728 %
a b c d e f g <-- classified as
124 0 0 0 1 0 0 | a = brickface
0 110 0 0 0 0 0 | b = sky
1 0 119 0 2 0 0 | c = foliage
1 0 0 107 2 0 0 | d = cement
1 0 12 7 105 0 1 | e = window
0 0 0 0 0 94 0 | f = path
0 0 1 0 0 2 120 | g = grass
b) 准确度:96.8 %
a b c d e f g <-- classified as
202 0 0 0 3 0 0 | a = brickface
0 220 0 0 0 0 0 | b = sky
0 0 198 0 10 0 0 | c = foliage
0 0 1 202 16 1 0 | d = cement
2 0 11 2 189 0 0 | e = window
0 0 0 2 0 234 0 | f = path
0 0 0 0 0 0 207 | g = grass
ETC...