The number of ice creams sold on a given day, based on the temperature, rainfall, and windspeed. The selling price of a property based on its size in square feet, the number of bedrooms it contains, and socio-economic metrics for its location. The fuel efficiency (in miles-per-gallon) ...
Learn about machine learning models: what types of machine learning models exist, how to create machine learning models with MATLAB, and how to integrate machine learning models into systems. Resources include videos, examples, and documentation covering
Common metrics for evaluating a model's performance include accuracy (for classification problems), precision and recall (for binary classification problems), and mean squared error (for regression problems). We cover this evaluation process in more detail in our Responsible AI webinar. Step 6: Hype...
Finally, alternative performance metrics may be required as reporting the classification accuracy may be misleading. Examples include: Precision. Recall. F-Measure. Next, let’s take a closer look at a dataset to develop an intuition for imbalanced classification problems. We can use the make_class...
[16]. On the other hand, some algorithms consider ensemble features from multiple aspects and build on top of existing pathogenicity prediction. For example, the Combined Annotation-Dependent Depletion (CADD) implements a support vector machine with annotation features in conservation metrics, ...
Machine Learning Maintenance Managed Network Fabric Managed Service Identity Maps MariaDB Marketplace Ordering Media Services Metrics Advisor Mixed Reality Mobile Network Mongo Cluster Monitor MySQL NetApp Files Network Network Analytics New Relic Observability News Search Nginx Notification Hubs Operator Nexus ...
68k Accesses 186 Citations 16 Altmetric Metrics details Abstract Incrementally learning new information from a non-stationary stream of data, referred to as ‘continual learning’, is a key feature of natural intelligence, but a challenging problem for deep neural networks. In recent years, ...
Diagnostic analytics helps answer questions about why things happened and is often the next step in data analytics after descriptive analytics. Analysts take findings from descriptive analytics and dig deeper to find the cause. Metrics and indicators of interest are further investigated to di...
3752 Accesses 3 Altmetric Metrics details Abstract A detailed understanding of herd types is needed for animal disease control and surveillance activities, to inform epidemiological study design and interpretation, and to guide effective policy decision-making. In this paper, we present a new approach ...
A system and method for accounting for the impact of concept drift in selecting machine learning training methods to address the identified impact. Pattern recognition is performed on performance metrics of a deployed production model in an Internet-of-Things (IoT) environment to determine the impact...