SAS' Sylvia Kabisa shows you how an online media company might use SAS to offer targeted discounts through personalized pricing.
Tag: Analytics R&D
Anuja Nagpal and Yonglin Zhu of SAS R&D reveal how, MLPA – without any code and within a given timeframe – finds an effective pipeline for a data set after applying data preprocessing, feature engineering and modeling with hyperparameter tuning.
SAS' Bahar Biller expounds on the idea that stochastic simulations are large-data generation programs for highly complex and dynamic stochastic systems.
Building on a previous post on how the seqmc action can be used to mine frequent sequences, SAS' Amod Ankulkar explores an alternative algorithm.
Using such features and Natural Language Processing capabilities like text parsing and information extraction in SAS Visual Text Analytics (VTA) helps us uncover emerging trends and unlock the value of unstructured text data.
To find exact duplicates, matching all string pairs is the simplest approach, but it is not a very efficient or sufficient technique. Using the MD5 or SHA-1 hash algorithms can get us a correct outcome with a faster speed, yet near-duplicates would still not be on the radar. Text similarity is useful for finding files that look alike. There are various approaches to this and each of them has its own way to define documents that are considered duplicates. Furthermore, the definition of duplicate documents has implications for the type of processing and the results produced. Below are some of the options. Using SAS Visual Text Analytics, you can customize and accomplish this task during your corpus analysis journey either with Python SWAT package or with PROC SQL in SAS.
SAS' Gunce Walton introduces to you a new scoring capability, how it utilizes Deep Neural Networks (DNNs) and shares use cases with PROC DEEPCAUSAL.
SAS' Damian Herrick chronicles the refresh of a 2002 social-network analysis aimed at identifying influential peer educators among former drug users.
In this introduction to powerful knowledge graph tools, SAS' Brandon Reese shows you how they can predict disease similarity and compound similarity using an unsupervised approach.
SAS' Bahar Biller reveals how simulations enable KPI generation, risk quantification, risk management and more.
SAS research statistician Ji Shen reveals how to train a machine to be a batting coach.
SAS' Michael Lamm gives an overview of Bayesian Additive Regression Trees (BART) and demonstrates training and scoring BART models in SAS Visual Statistics.
SAS' Jordan Leiker shows you how any CAS action can be used with image data to create heat maps.
In the second of two Q&As with R&D colleagues, SAS' Udo Sglavo provides a window into how we approach drug-development challenges with machine learning.
A note from Udo Sglavo: At SAS, what we deliver to our customers is a product of creative minds thinking differently, challenging the norm, taking risks, and learning from trial and error (The greatest teacher, failure is). For the return of World Creativity & Innovation Week, we want to share
SAS' Brian Gaines provides a primer on GAMs.
SAS' Xuejun Liao weighs the pros and cons of collaborative filtering and supervised learning and explores their use in a unified framework.
SAS' Courtney Ambrozic highlights how to use SAS VDMML to assess lesion response to chemotherapy for patients with colorectal liver cancer.
SAS' Pankaj Telang shows you new image-specific processing capabilities in SAS Visual Data Mining and Machine Learning.
SAS' Kelly Fellingham, an advanced analytics software developer, reveals how SAS software's new SASEBEA interface helps you identify patterns in US economics data.
In a Q&A with SAS' Udo Sglavo, Xilong Chen of SAS parses the work of 2021 Nobel Prize winners for Economics.
SAS' Hamza Ghadyali introduces you to JupICL, a SAS field-tested, easy-to-use, customizable image labelling tool that runs entirely inside a Jupyter notebook.
SAS' Rajesh Selukar introduces you to a new scoring feature.
SAS' Bahar Biller, an operations researcher, details how to develop a supply chain digital twin.