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The advantage of using SAS PROC KPCA is that you can preprocess your data so that you can classify groups with nonlinear classification boundaries.
SAS® Fast-KPCA implementation bypasses the limitations of exact KPCA methods. SAS® internally uses k-means to find a representative sample of a subset of points. This row reduction method has the advantage that c centroids are chosen to minimize the variation of points nearest to each centroid and maximize the variation to the other cluster centroids. In some cases, the downstream effect of using k-means on computing the SVD increases numerical stability and improves clustering, discrimination, and classification.
Mesmo com a tecnologia disponível atualmente, é muito difícil prever quando, onde e como podem ocorrer danos causados pelo clima. Custos com inundações devem crescer exponencialmente nos próximos 20 anos e a crise climática é uma ameaça constante. Infelizmente, desastres naturais nunca deixarão de existir, mas podemos fazer nosso melhor
I will show you how to deploy multi-stage deep learning (DL) models in SAS Event Stream Processing (ESP) and leverage ESP on Edge via Docker containers to identify events of interest.
Fraud detection is becoming increasingly more complex. Customers are demanding a frictionless consumer experience. Luckily, SAS' advanced machine learning models can better prevent fraud and protect customers by analyzing behaviors and detecting suspicious patterns in real-time.
In the competitive and highly regulated insurance industry, it’s easy to see why firms are hungry to unlock the value of their data. From tackling claims inflation and fraud to developing innovative new products and pricing strategies, they know that being able to make sense of this data quickly is
Using SAS Viya in combination with open-source capabilities, we were able to develop an automated solution for logo detection that does not require any manual data labeling.
Quando a pandemia do COVID-19 atingiu a Indonésia, bloqueios e restrições de atividade fecharam grande parte do comércio, ameaçando o sustento de milhões de pessoas. Isso porque o país possui mais de 64 milhões de micro, pequenas e médias empresas (MPMEs), responsáveis por empregar 97% da força de trabalho do
Estudos indicam que, ao longo dos últimos anos, aumentaram os casos de propagação de discursos de ódio e de notícias falsas. Especialmente no ano de 2022 há uma preocupação muito grande quanto à utilização desses recursos ilegítimos para finalidades eleitorais. Técnicas analíticas podem ser empregadas para estimular campanhas eleitorais que
The IEEE Visual Analytics Science and Technology (VAST) Challenge provides a great opportunity to validate our software against real-world scenarios using complex data sets. Not only do we learn from these projects, but we also send feedback to our development teams to further improve product capabilities for customers.
Let's create a Multi-stage Computer Vision model to detect objects on high-resolution imagery taken from an aerial view. The goal is to locate a dog and determine if he is wearing a scarf or not and what color the scarf is.
It’s hard to get through a day in analytics now without hearing the words interpretability and explainability. These terms have become important in a world where machine learning and artificial intelligence (AI) models are becoming more ubiquitous. However, what do the two terms mean—and more importantly, why do they matter?
Para los defraudadores y blanqueadores de fondos, el lavado de dinero es una mina de oro altamente redituable. Se calcula que entre el 2% y el 5% del producto interno bruto (PIB) global es lavado, lo que representa casi $3,000 millones de dólares (mdd) de fondos ilícitos que se fluyen
This year we had the pleasure to attend the 42nd International Symposium on Forecasting in Oxford, UK. SAS participants traveled from across the globe. They presented their research, discussed their ideas, and learnt from some of the most reputable names in the forecasting space. The presentations were captivating and the
Often the biggest challenge when implementing a successful forecasting process has nothing to do with the analytics. Forecast adoption – incorporating forecasts into decision-making – is just as high a hurdle to overcome as the models themselves. Forecasting is more than analytical models Developing a forecasting process typically begins with
Las organizaciones están bastante conscientes de que las cosas pueden cambiar radicalmente en cuestión de semanas. La experiencia de los dos últimos años les ha hecho reconocer la necesidad de tener la capacidad de tomar decisiones inteligentes a partir de datos confiables que puedan llevar a resultados positivos. En este
Robert Handfield, PhD, is a distinguished professor of Supply Chain Management at North Carolina State University and Director of the Supply Chain Resource Cooperative. In an episode of the Health Pulse Podcast, Handfield gave his views regarding the challenges health care and life science companies have encountered over the past two years
Wouldn’t it be cool if we establish a mechanism that provides more data scientists easy access to SAS Reinforcement Learning capabilities, from a centralized location and using a standardized approach?
Becoming a parent is one of the most exciting things in life. Unfortunately, sometimes pregnancy complications occur, remaining a serious challenge, that is not often talked about. Ahead are interviews with leading researchers in Dublin aimed to understand the impact of data and analytics on maternal health. According to the
Los habitantes del planeta están cada vez más conectados. Se estima que actualmente el número de usuarios de teléfonos inteligentes a escala global supera la marca de los 3,000 millones, y que esta cantidad siga creciendo paulatinamente en los próximos años. Tal cantidad de usuarios demanda cada vez más de
There’s plenty of buzz about innovation and thinking outside of the box at SAS these days. But for those who attended SAS' Patent Dinner, the proof was in the patent. SAS Legal Counsel Director Tim Wilson offered opening remarks at The Umstead event. “So much of what we do in
As promised in this latest blog about the Gartner Data & Analytics Summit in London, here’s an update from the second day at the SAS booth. To make a long story short, each day the SAS booth team posed a question to attendees visiting the booth. They could submit three
Toc, toc, toc. En algún lugar de Berlín a comienzos del siglo XX, tras esos pequeños tres golpes, se podía observar inconfundibles caras de asombro entre los periodistas y curiosos. En cambio, Wilhelm Von Osten reflejaba en su rostro algo más: felicidad, realización y por qué no, el disfrute de
Just getting started with this series? Make sure to explore the earlier posts Part 1, Part 2 and Part 3. Up until now, you have seen how ModelOps can solve your biggest machine learning challenges and that SAS and Microsoft, together, can help you deploy, govern and monitor your models
We hear a lot about responsible AI or AI ethics in the marketplace today. At SAS, we believe there should be a larger conversation about responsible innovation. In reality, the decisions made by AI are the outcome of algorithms, data and business processes. This means ethical considerations must be applied
Just getting started with this series? Make sure to explore Part 1 and Part 2. There are different ways you can use these two tools to accelerate model building, deployment and monitoring. Figure 1 summarizes best practices for conducting ModelOps using SAS Model Manager and Azure Machine Learning. Best practice
Just getting started with this series? Make sure to read part 1: How ModelOps addresses your biggest Machine Learning challenges. SAS and Microsoft make it easier for companies to address the challenges of machine learning model deployment, monitoring and governance. Specifically, SAS and Microsoft have built integrations between SAS® Model
Editors note: This is the first in a series of articles. According to the Global McKinsey Survey on the State of AI in 2021, the adoption of AI is continuing to grow at an unprecedented rate. Fifty-six percent of all respondents reported AI adoption – including machine learning (ML) –
La tecnología o la experiencia de cliente son algunos de los factores que más peso están adquiriendo en la evolución que vive el sector Seguros. Así, en los últimos años estamos observando un interés cada vez mayor en la ciencia de datos y aplicaciones de machine learning de las compañías
If you are an Enterprise Miner user, do not miss the opportunity to try out Model Studio in SAS Viya. I am sure you will love it!
