If you are modeling binomial data; ie a numerator consisting of the number of 1/0 successes you have for a given pattern of covariates, and a denominator that gives the value of the total number of observations having that covariate pattern (a specific profile of predictor values; eg age 23, married 1, working 0), a logistic regresson is generally appropriate. But when the mean values of the numerators are less than 10% of the mean values of the denominator, it is likely that a Poisson model is preferred. The otherwise logistic numerator is the count response variable (dependent variable) and the natural log of the denominator is the offset. Generally the Poisson model will fit the data better. Logistic models are not indended for rare occurrences.

Toyota Motor and Suzuki, citing the major changes faced by the global auto industry and the need to bundle industry-wide R&D resources, said they are exploring a business partnership. The two automakers provided little detail on the nature of their talks, but said in a press release that, next to traditional areas of R&D focus, it is increasingly important to work together with other companies on areas such as infrastructure development, as well as the establishment of new industrial standards. Toyota is the worlds biggest automotive group, with a presence in virtually all car segments. Suzuki is much smaller but has a strong position in small cars, especially in Japan and India. It has a dominant share of the rapidly expanding Indian market through a partnership with local producer Maruti.

Donald Trump could be planning to launch a TV station soon after the election, according to new reports. Some have suggested that Mr Trump's plan for Trump TV might be his way of seizing on the fans he has cultivated as part of his election campaign. Mr Trump's campaign may even be partly motivated by a potential plan to establish a media empire, others have said. Mr Trump's son-in-law and adviser Jared Kushner has approached the head of LionTree, an investment bank experienced in media deals, according to the Financial Times. The conversation was brief and hasn't moved on since they spoke in the last couple of months, the paper reported, but Mr Kushner may have consulted with other people in the time since.

Tesla's much-anticipated new product announcement has been delayed by two days. Elon Musk was due to unveil an'unexpected product' later today. But the Tesla CEO said the big reveal will now take place on Wednesday as the secret product still needs some work. While Tesla is best known for its electric cars, the company has new products on the way. Many people on Twitter have speculated at what the new product could be.

KARIYA, Japan & TOKYO--(BUSINESS WIRE)--DENSO Corporation and Toshiba Corporation have reached a basic agreement to jointly develop an artificial intelligence technology called Deep Neural Network-Intellectual Property (DNN-IP), which will be used in image recognition systems which have been independently developed by the two companies to help achieve advanced driver assistance and automated driving technologies. DNN, an algorithm modeled after the neural networks of the human brain, is expected to perform recognition processing as accurately as, or even better than the human brain. To achieve automated driving, automotive computers need to be able to identify different road traffic situations including a variety of obstacles and road markings, availability of road space for driving, and potentially dangerous situations. In image recognition based on conventional pattern recognition and machine learning, objects that need to be recognized by computers must be characterized and extracted in advance. In DNN-based image recognition, computers can extract and learn the characteristics of objects on their own, thus significantly improving the accuracy of detection and identification of a wide range of objects.

Apple will celebrate the iPhone's 10th anniversary next year, but in chief executive Tim Cook's view, the technology is anything but mature. The Nikkei Asian Review caught up with Cook aboard a bullet train last week and asked him about artificial intelligence, his plans for Asia, and the experience of succeeding Steve Jobs. Cook, who was visiting Japan for the first time as CEO, said Apple will open a research and development base in Yokohama, near Tokyo, later this year. The facility -- the first of its kind outside the U.S. -- will develop AI and other technologies. Cook described it as a center for "deep engineering" and said it will be "very different" from the R&D base Apple plans to build in China. "I cannot tell you the specifics," he said.

Cluster analysis is a staple of unsupervised machine learning and data science. It is very useful for data mining and big data because it automatically finds patterns in the data, without the need for labels, unlike supervised machine learning. In a real-world environment, you can imagine that a robot or an artificial intelligence won't always have access to the optimal answer, or maybe there isn't an optimal correct answer. You'd want that robot to be able to explore the world on its own, and learn things just by looking for patterns. Do you ever wonder how we get the data that we use in our supervised machine learning algorithms?

Watson, can you grow into a multibillion-dollar business and become the engine of IBM's resurgence? IBM is betting its future that the answer is yes. Its campaign to commercialize Watson, the company's version of artificial intelligence technology, stands out, even during the current A.I. frenzy in the tech industry. IBM has invested billions of dollars in its Watson business unit, created at the start of 2014, which now employs an estimated 10,000 workers. Its big-ticket marketing push includes clever television ads that feature Watson trading quips with famous people like Serena Williams and Bob Dylan.

In Part 1 of this tutorial series, we gave an overview of cognitive computing and provided examples of how cognitive computing is being used to create industry solutions. We also determined a need for a cognitive platform to implement these solutions. The benefits of a cognitive solution include the reuse of components, faster development of the solution, and reduced costs. The key to creating such a platform includes the ability to run multiple use cases on the platform. Therefore, it is critical to identify these use cases and determine how a platform can provide benefits when implemented.

Which authors of this paper are endorsers? Disable MathJax (What is MathJax?)