Machine Learning with R

By J. Bell. 2015

328 citations recorded by the source corpus.

Subfields: Artificial Intelligence

View Paper: https://www.semanticscholar.org/paper/40c9b59c95ab1c98d6b4ef3c514a5db3a9b8ccb7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Davide Chicco
2. Scott Sanner
3. Chi-Guhn Lee
4. Michael Gimelfarb
5. Giuseppe Jurman
6. Oguzhan Gencoglu

Citations in the corpus

• Ten quick tips for machine learning in computational biology (2017, methodology): “For these and other reasons, we advice you to work only with free open source machine learning software packages and platforms, such as R [46], Python [47], Torch [48], and Weka [49].”
• Reinforcement Learning with Multiple Experts: A Bayesian Model Combination Approach (2018, methodology): “Lantz [2013]). Hidden neurons use leaky ReLU activations and outputs use linear to allow unbounded values. The learning rate is fixed at 0.001 throughout training that is done on-line using the Adam optimizer in batches of size 16 sampled randomly from memory of size 10000 (we found that doing 5 epo”