文件名称:PCA+mnist
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基于python，利用主成分分析（PCA）和K近邻算法（KNN）在MNIST手写数据集上进行了分类。
经过PCA降维，最终的KNN在100维的特征空间实现了超过97%的分类精度。(Based on python, it uses principal component analysis (PCA) and K nearest neighbor algorithm (KNN) to classify on the MNIST handwritten data set.
After PCA dimensionality reduction, the final KNN achieved a classification accuracy of over 97% in a 100-dimensional feature space.)
经过PCA降维，最终的KNN在100维的特征空间实现了超过97%的分类精度。(Based on python, it uses principal component analysis (PCA) and K nearest neighbor algorithm (KNN) to classify on the MNIST handwritten data set.
After PCA dimensionality reduction, the final KNN achieved a classification accuracy of over 97% in a 100-dimensional feature space.)
相关搜索： PCA降维；KNN分类；mnist手写体
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下载文件列表
| 文件名 | 大小 | 更新时间 |
|---|---|---|
| pca.py | 2057 | 2020-10-17 |
| t10k-images-idx3-ubyte.gz | 1648877 | 2018-10-10 |
| t10k-labels-idx1-ubyte.gz | 4542 | 2018-10-10 |
| train-images-idx3-ubyte.gz | 9912422 | 2018-10-10 |
| train-labels-idx1-ubyte.gz | 28881 | 2018-10-10 |