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What's SAS doing at KDD 2014?

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What's SAS doing at KDD 2014?

If you're headed to KDD 2014 on Aug. 24-27 in New York City, be sure to stop by the SAS booth - #14. SAS will present a paper and tons of "super demos" at the booth. Here are the details.

Paper:

Research 4: Feature Selection
Monday, August 25, 10:30 a.m. - 12 p.m. - Riverside Ballroom

Safe and Efficient Screening For Sparse Support Vector Machine

Zheng Zhao, SAS Institute Inc; Jun Liu, SAS Institute Inc; James Cox, SAS Institute Inc;

15-minute super demos of new features:

Monday, August 25, 10:00-10:15 a.m.

Deep Learning for Dimensionality Reduction/Visualization

Jorge Silva

We will showcase deep learning with PROC NEURAL, using a deep auto-encoder architecture to visualize clustering results on medical provider data.


Monday, August 25, 1:00-1:15 p.m.

Contextual Recommendation Using Text Analysis

Yue Qi

The collaborative filtering-based recommender is prone to the cold start problem and long tail problem, so this demo will show how to derive contextual recommendations using text analysis to address both problems.


Monday, August 25, 3:00-3:15 p.m.

Time Series Dimension Reduction for Data Mining Using SAS®

Catherine Lopes

This demo introduces SAS procedures for time series dimension reduction in data mining.


Monday, August 25, 5:00-5:15 p.m.

New Techniques for Doing Association Classification and a Demonstration of Their Usefulness for Mining Text

Jim Cox

We will describe two new algorithms for pattern discovery with a single consequent or external category: Bool-yer and AssoCat.


Tuesday, August 26, 10:00-10:15 a.m.

R Integration Node

Jorge Silva

This demo will illustrate the diagram and workflow user interface and also focus on how people can try their favorite R algorithms while taking advantage of data handling and pre-processing capabilities built into SAS® Enterprise Miner.


Tuesday, August 26, 1:00-1:15 p.m.

Classification Using Bayesian Networks in SAS Enterprise Miner

Weihua Shi

Using a newly developed high-performance Bayesian network procedure (PROC HPBNET), this demo will illustrate the graphic modeling approach using real-world data.


Tuesday, August 26, 3:00-3:15 p.m.

Interactive Stratified Modeling Using SAS® Visual Statistics

Wayne Thompson

This demo will show how to develop stratified models based on group-by variables, decision trees to derive segments and enforce business rules, and clustering demographic data followed by supervised models using transactional data.

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