A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Machine Learning: A Basic Overview
Machine learning (ML) generally refers to the development of methods that optimize their performance iteratively by “learning from the data”. ML is broadly understood as a group of methods that analyze data and make useful discoveries and inferences from the data. It relies heavily on techniques and theory from statistics, optimization, algorithms, and biologically inspired systems. ML can be classified into four groups: supervised learning, unsupervised learning, semi‐supervised learning, and reinforcement learning. The semi‐supervised learning methods come from a collection of cases where only parts of them have assigned labels. Processing railway track data is becoming more complex. Kernel methods are an example of the ML techniques that are very effective for feature extraction. Kernel methods use kernel techniques to implicitly map input patterns to a feature space. Imbalanced classification is a supervised learning problem where one class outnumbers the other class by an extremely large population.
Machine Learning: A Basic Overview
Machine learning (ML) generally refers to the development of methods that optimize their performance iteratively by “learning from the data”. ML is broadly understood as a group of methods that analyze data and make useful discoveries and inferences from the data. It relies heavily on techniques and theory from statistics, optimization, algorithms, and biologically inspired systems. ML can be classified into four groups: supervised learning, unsupervised learning, semi‐supervised learning, and reinforcement learning. The semi‐supervised learning methods come from a collection of cases where only parts of them have assigned labels. Processing railway track data is becoming more complex. Kernel methods are an example of the ML techniques that are very effective for feature extraction. Kernel methods use kernel techniques to implicitly map input patterns to a feature space. Imbalanced classification is a supervised learning problem where one class outnumbers the other class by an extremely large population.
Machine Learning: A Basic Overview
Attoh‐Okine, Nii O. (author)
Big Data and Differential Privacy ; 59-111
2017-06-26
53 pages
Article/Chapter (Book)
Electronic Resource
English
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