搜索资源列表
cohenKappa
- Calcuate Cohen s kappa statistics from a confusion matrix
cfmatrix
- 本程序，可以用了画混淆矩阵，请大家使用，-This procedure can be painted with a confusion matrix, please use, thanks
BayeClassifier
- Bayesian calssifier matlab code and confusion matrix
6d85523f7a9f
- Implementation of Confusion matrix in python
EBONE
- computes confusion matrix from classified data sets
confusionMatrix3d
- 显示一个3 D的混淆矩阵,并返回深入全面的统计和统计每组氮组。-Displays a 3D confusion matrix, and returns thorough overall stats and stats per group for N groups.
confusionMatrix3d_
- 总体PCC和集团统计混淆矩阵3D 显示一个3D混淆矩阵，并返回N组深入每个组的整体统计和统计-Confusion Matrix 3D with Overall PCC and Group Statistics
plotreliability
- Confusion matrix matlab
confusion-matrix
- 对识别结果进行混合矩阵分析，从而显示识别精度-generates a confusion matrix
Confusion-matrix
- This file displays the Confusion matrix, which is always used to show the error according to each class.
Performance
- 计算分类性能指标matlab代码，指标包涵：混淆矩阵ConfusionMatrix 整体分类精度OA Kappa 平均精度AA 用户精度user 生产精度producer 每个类别的准确率perAcc -Classification performance computing matlab code, index inclusion: confusion matrix ConfusionMatrix overall classification accuracy OA Kappa
confusionmatSen
- example fi e for calculate sensitivity by confusion matrix
confusion-matrix
- This code is designed for two or more classes instance confusion matrix formation and Calclating 1acuuracy 2.error 3.Sensitivity (Recall or True positive rate) 4.Specificity 5.Precision 6.FPR-False positive rate 7.F_score
cloudy
- confusion matrix feature selection in clody system matlab
confusion-matrix
- 模式识别中可用来计算精度、错误率，敏感性、以及假阳性等-In the pattern recognition can be used to calculate the precision, error rate, sensitivity, and a false positive
PG_Curve-master
- 根据得到的分类标签，画出分类结果的混淆矩阵(Draw a confusion matrix of classification results)
confusion_matrix1
- 只有一个文件，调用函数即可生成混淆矩阵，参数可在文件中更改(Call the function to generate a confusion matrix, parameters can be changed in the file)
vtshitoyan-plotConfMat-1787253
- 就是用MATLAB绘制,一个颜色编码的混淆矩阵。(MATLAB is used to draw a color coded confusion matrix.)
sklearn-SVM
- 支持向量机(SVM)——分类预测，包括核函数调参，不平衡数据问题，特征降维，网格搜索，管道机制，学习曲线，混淆矩阵，AUC曲线等(Support vector machine (SVM) - classification prediction, including kernel function parameter adjustment, unbalanced data problem, feature dimensionality reduction, grid search, pipelin