clip2frame.measure¶
mean_auc_y(Y_target, Y_score) |
along y-axis |
mean_auc_x(Y_target, Y_score) |
along x-axis |
map_y(Y_target, Y_score) |
|
map_x(Y_target, Y_score) |
|
f1_micro(y_target, y_predicted) |
y_target: m x n 2D array. {0, 1} |
f1_macro(y_target, y_predicted) |
y_target: m x n 2D array. {0, 1} |
precision_micro(y_target, y_predicted) |
y_target: m x n 2D array. {0, 1} |
precision_macro(y_target, y_predicted) |
y_target: m x n 2D array. {0, 1} |
recall_micro(y_target, y_predicted) |
y_target: m x n 2D array. {0, 1} |
recall_macro(y_target, y_predicted) |
y_target: m x n 2D array. {0, 1} |
Details¶
-
clip2frame.measure.f1_micro(y_target, y_predicted)[source]¶ - y_target: m x n 2D array. {0, 1}
- real labels
- y_predicted: m x n 2D array {0, 1}
- prediction labels
m (y-axis): # of instances n (x-axis): # of classes
-
clip2frame.measure.f1_macro(y_target, y_predicted)[source]¶ - y_target: m x n 2D array. {0, 1}
- real labels
- y_predicted: m x n 2D array {0, 1}
- prediction labels
m (y-axis): # of instances n (x-axis): # of classes
-
clip2frame.measure.precision_micro(y_target, y_predicted)[source]¶ - y_target: m x n 2D array. {0, 1}
- real labels
- y_predicted: m x n 2D array {0, 1}
- prediction labels
m (y-axis): # of instances n (x-axis): # of classes
-
clip2frame.measure.precision_macro(y_target, y_predicted)[source]¶ - y_target: m x n 2D array. {0, 1}
- real labels
- y_predicted: m x n 2D array {0, 1}
- prediction labels
m (y-axis): # of instances n (x-axis): # of classes