[SPARK-2623] Stacked Auto Encoder (Deep Learning )

• Type: New Feature
• Status: Resolved
• Priority: Major
• Resolution: Duplicate
• Component/s: MLlib
• Labels: deeplearning machine_learning
• Assignee: Apache Spark
• Reporter: Victor Fang
• Created: 22/Jul/14 17:26
• Updated: 13/Sep/16 08:30
• Resolved: 13/Sep/16 08:30

Description

We would like to add parallel implementation of Stacked Auto Encoder (Deep Learning ) algorithm to Spark MLLib.
SAE is one of the most popular Deep Learning algorithms. It has achieved successful benchmarks in MNIST hand written classifications, Google's ICML2012 "cat face" paper (http://icml.cc/2012/papers/73.pdf), etc.
Our focus is to leverage the RDD and get the SAE with the following capability with ease of use for both beginners and advanced researchers:
1, multi layer SAE deep network training and scoring.
2, unsupervised feature learning.
3, supervised learning with multinomial logistic regression (softmax).

Issue Links

• duplicates: SPARK-10408 Autoencoder
• is part of: SPARK-10408 Autoencoder
• relates to: SPARK-5575 Artificial neural networks for MLlib deep learning
• links to: [Github] Pull Request #13621 (avulanov)