[{"title":"( 10 个子文件 4.99MB ) 使用K-NN、朴素贝叶斯及最小欧氏距离进行高光谱图像分类,准确度和混淆矩阵评估模型,运行project.m即可","children":[{"title":"naive_bayes.m <span style='color:#111;'> 5.59KB </span>","children":null,"spread":false},{"title":"plot_dataset.m <span style='color:#111;'> 1.82KB </span>","children":null,"spread":false},{"title":"Salinas_hyperspectral.mat <span style='color:#111;'> 4.98MB </span>","children":null,"spread":false},{"title":"project.m <span style='color:#111;'> 3.82KB </span>","children":null,"spread":false},{"title":"k_nn.m <span style='color:#111;'> 2.43KB </span>","children":null,"spread":false},{"title":"classification_labels.mat <span style='color:#111;'> 6.10KB </span>","children":null,"spread":false},{"title":"k_nn_algorithm.m <span style='color:#111;'> 1.32KB </span>","children":null,"spread":false},{"title":"classifier_stats.m <span style='color:#111;'> 449B </span>","children":null,"spread":false},{"title":"minimum_euclidean_distance.m <span style='color:#111;'> 4.18KB </span>","children":null,"spread":false},{"title":"k_nn_5_fold_cross_validation.m <span style='color:#111;'> 8.99KB </span>","children":null,"spread":false}],"spread":true}]