A method of selecting a model of machine learning executed by a processor is provided. The method includes: receiving at least one data-set; configuring a configuration space for machine learning of the at least one data-set; extracting, from the at least one data-set, a meta-feature ...
Can an algorithm assist firms in their hiring decisions of corporate directors? This paper proposes a method of selecting boards of directors that relies on machine learning. We develop algorithms with the goal of selecting directors that would be preferred by the shareholders of a particular firm....
An Improved Machine Learning Approach for Selecting a Polyhedral Model TransformationAlgorithms in fields like image manipulation, signal processing, and statistics frequently employ tight CPU-bound loops, whose performance is highly dependent on efficient utilization of the CPU and memory bus. The ...
AutoAI automatically prepares data, applies algorithms, and attempts to build model pipelines best suited for your data and use case. This topic describes how to evaluate the model pipelines. During AutoAI training, your data set is split to a training part and a hold-out part. The training ...
Learning Meta-descriptions of the FOAF Network We argue that in a distributed context, such as the Semantic Web, ontology engineers and data creators often cannot control (or even imagine) the possible uses their data or ontologies might have. Therefore ontologies are unlikely to ide... GA Grim...
and CPU and memory utilization. Given that machine learning tasks can quickly reach several thousands of dollars, focus on optimal infrastructure costs for specific requirements. CloudWatch metrics are an essential tool to assess if a particular instance type is the right one for a particular...
The key problem of word sense disambiguation based on statistic model lies in how to acquiring the word sense indicators automatically. Although it is feasible to acquire a large number of collocations by learning examples, it is hard to select good seeds manually to increase new collocations effec...
A profile model can be selected for use in examining a structure formed on a semiconductor wafer using optical metrology by obtaining an initial profile model having a set of profile parameters. A machine learning system is trained using the initial profile model. A simulated diffraction signal is...
Nvidia Corp. (NVDA): The company is well-known for its advanced graphics processing units, a crucial element for AI and machine learning applications. Its latest AI chips are considered highly powerful, augmenting its already-strong position in the AI market.22 ...
To estimate classification complexity in different feature subspaces, a novel feature evaluation measure, called the neighborhood decision error rate (NDER), is proposed, which is applicable to both categorical and numerical features. We first introduce a neighborhood rough-set model to divide the ...