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- mRMR特征选择方法,[ 软件使用方法] ( https://github.com/csuldw/MachineLearning/tree/master/mRMR )
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- - 机器学习算法代码使用汇总,[ Python & R Codes] ( http://csuldw.github.io /2015/11/21/2015-11-21-machine-learning-algorithms/ )
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+ - 机器学习算法代码使用汇总,[ Python & R Codes] ( http://www. csuldw.com /2015/11/21/2015-11-21-machine-learning-algorithms/ )
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- PCA主要成分分析, [ Python实现源码] ( https://github.com/csuldw/MachineLearning/tree/master/PCA )
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在学习机器学习的时候,首当其冲的就是准备一份通用的数据集,方便与其他的算法进行比较。在这里,我写了一个用于加载MNIST数据集的方法,并将其进行封装,主要用于将MNIST数据集转换成numpy.array()格式的训练数据。直接下面看下面的代码吧!
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- 文章链接:[ 机器学习数据集-MNIST] ( http://csuldw.github.io /2016/02/25/2016-02-25-machine-learning-MNIST-dataset/ )
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+ 文章链接:[ 机器学习数据集-MNIST] ( http://www. csuldw.com /2016/02/25/2016-02-25-machine-learning-MNIST-dataset/ )
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MNIST数据集原网址:[ http://yann.lecun.com/exdb/mnist/ ] ( http://yann.lecun.com/exdb/mnist/ )
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