Category: Machine learning
The dropout approach developed by Hinton has been widely employed in deep learnings to prevent the deep neural network from overfitting, as shown in https://statcompute.wordpress.com/2017/01/02/dropout-regularization-in-deep-neural-networks. In the paper http://proceedings.mlr.press/v38/korlakaivinayak15.pdf, the...continue reading.
In my early post (https://statcompute.wordpress.com/2017/01/22/monotonic-binning-with-smbinning-package/), I wrote a monobin() function based on the smbinning package by Herman Jopia to improve the monotonic binning algorithm. The function works well and provides...continue reading.
Running R on the cloud isn’t very difficult. This demo shows how to get Rstudio running on Amazon Web Services. To run R on the cloud we need to initiate...continue reading.
When taking advanced analytics to the cloud you’ll need a strong understanding of your platform – whether it’s compute, storage, or some other feature. This tutorial walks you through reading...continue reading.
Since CNN(Convolutional Neural Networks) have achieved a tremendous success in various challenging applications, e.g. image or digit recognitions, one might wonder how to employ CNNs in classification problems with binary...continue reading.