Since CALO has many learning systems, one challenge is integrating them so that CALO has a consistent structure for information that it can use to make decisions based on the noisy, uncertain data that it extracts from its various interactions.
GULLIVER is based on a decision-making module integrating uncertain data coming from observation of the learner by the system.
The deep learning models are initially developed from certain data and gradually evolve with uncertain data to effectively reduce big data streams.
However, some elements may involve uncertain data in practice.
Producing accessible and unbiased visualisations from complicated, uncertain data requires expertise and knowledge from science, policy, computing, and design.
Fuzzy logic offers a linguistic (approximate) way of drawing conclusions from uncertain data, and neural networks offer the capability of learning and training with or without a teacher (supervisor).
This book examines all aspects essential for a successful application of geometric algebra: the theoretical foundations, the representation of geometric constraints, and the numerical estimation from uncertain data.
In [105], the authors firstly discussed the sources of data uncertainty and gave some examples and then devised an algorithm for building decision trees from uncertain data using the distribution-based approach.
Leung et al. in [18] proposed an algorithm that reduces the search space based on the user-specified constraints and uses the MapReduce model to discover interesting patterns from uncertain data which satisfies those constraints.
Apart from uncertain data, our wage/remuneration cost comparisons are limited by differential work loads, as noted above, and the two systems being at different stages of transferring tasks from physicians to other professionals.
Due to the pervasive data uncertainty in many real applications, efficient and effective query answering on uncertain data has recently gained much attention from the database community.
