Now, this unlabelled input data is fed to the machine learning model to train it. Firstly, it will interpret the raw data to find the hidden patterns from the data and then will apply suitable …

In this knowledge entry, the fundamentals of Machine Learning (ML) are introduced, focusing on how feature spaces, models and algorithms are being developed and applied in geospatial …

The commonly used machine learning algorithms, evaluation methods, and validation approaches are presented. The emerging issues and future directions are discussed accordingly.

Goal: Why the learning is done. The learning can be done to retrieve a set of rules from spurious data, to become a good simulator for some physical phenomenon, to take control over a …

The review of all the four types Machine learning techniques has been discussed in this paper. These techniques are different from each other in every aspect, either in terms of applications, …

Obviously, there are trade-offs between the various approaches. For instance, increasing map size with exploration may eventually overload a system’s storage space, while only modeling

This comprehensive categorization provided in Table 2 allows for a systematic comparison of the reviewed studies, highlighting similarities and differences in methodologies, data sources, and …