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Results tagged with semi-supervised-learning
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user 212133
Semi-supervised learning refers to machine learning tasks using a mix of labeled and unlabeled data. The goal is to learn a mapping from inputs to outputs, or to obtain outputs for particular unlabeled inputs. The unlabeled data is used to learn about underlying structure of the inputs, which can improve learning about the relationship between inputs and outputs. Semi-supervised learning involves elements of both supervised and unsupervised learning.
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Does it make sense to use feature selection methods to reduce dimensionality for unsupervise...
You can perform dimensionality reduction in an unsupervised manner such as using PCA. You can then perform clustering in as many components as you need. Be cautious of the information gain for each PC …
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