论文标题
主成分分类
Principal Component Classification
论文作者
论文摘要
我们建议通过使用PCA使用其类得分编码的学习功能直接计算分类估计。我们最终的模型具有适用于监督学习的编码器结构，它在计算上是有效的，并且在几个数据集上的分类表现良好。
We propose to directly compute classification estimates by learning features encoded with their class scores using PCA. Our resulting model has a encoder-decoder structure suitable for supervised learning, it is computationally efficient and performs well for classification on several datasets.
