ee.ConfusionMatrix

创建混淆矩阵。矩阵的轴 0（行）对应于实际值，轴 1（列）对应于预测值。

用法	返回
ee.ConfusionMatrix(array, order)	ConfusionMatrix

参数	类型	详细信息
array	对象	一个表示混淆矩阵的整数二维方阵。请注意，与 ee.Array 构造函数不同，此实参不能采用列表。
order	列表，默认值：null	非连续或非零基准矩阵的行和列大小及顺序。

示例

代码编辑器 (JavaScript)

// A confusion matrix. Rows correspond to actual values, columns to
// predicted values.
var array = ee.Array([[32, 0, 0,  0,  1, 0],
                      [ 0, 5, 0,  0,  1, 0],
                      [ 0, 0, 1,  3,  0, 0],
                      [ 0, 1, 4, 26,  8, 0],
                      [ 0, 0, 0,  7, 15, 0],
                      [ 0, 0, 0,  1,  0, 5]]);
print('Constructed confusion matrix',
      ee.ConfusionMatrix(array));

// The "order" parameter refers to row and column class labels. When
// unspecified, the class labels are assumed to be a 0-based sequence
// incrementing by 1 with a length equal to row/column size.
print('Default row/column labels (unspecified "order" parameter)',
      ee.ConfusionMatrix({array: array, order: null}).order());

// Set the "order" parameter when custom class label integers are required. The
// list of integer value labels should correspond to the matrix axes left to
// right / top to bottom.
var order = [11, 22, 42, 52, 71, 81];
print('Specified row/column labels (specified "order" parameter)',
      ee.ConfusionMatrix({array: array, order: order}).order());

Python 设置

如需了解 Python API 和如何使用 geemap 进行交互式开发，请参阅 Python 环境页面。

import ee
import geemap.core as geemap

Colab (Python)

from pprint import pprint

# A confusion matrix. Rows correspond to actual values, columns to
# predicted values.
array = ee.Array([[32, 0, 0,  0,  1, 0],
                  [ 0, 5, 0,  0,  1, 0],
                  [ 0, 0, 1,  3,  0, 0],
                  [ 0, 1, 4, 26,  8, 0],
                  [ 0, 0, 0,  7, 15, 0],
                  [ 0, 0, 0,  1,  0, 5]])
print('Constructed confusion matrix:')
pprint(ee.ConfusionMatrix(array).getInfo())

# The "order" parameter refers to row and column class labels. When
# unspecified, the class labels are assumed to be a 0-based sequence
# incrementing by 1 with a length equal to row/column size.
print('Default row/column labels (unspecified "order" parameter):',
      ee.ConfusionMatrix(array, None).order().getInfo())

# Set the "order" parameter when custom class label integers are required. The
# list of integer value labels should correspond to the matrix axes left to
# right / top to bottom.
order = [11, 22, 42, 52, 71, 81]
print('Specified row/column labels (specified "order" parameter):',
      ee.ConfusionMatrix(array, order).order().getInfo())