In semi-supervised classification, both labeled and unlabeled data are used to train a classifier. This learning paradigm has obtained promising results, specifically in the presence of a …

ssc: Semi-Supervised Classification Methods. Provides a collection of self-labeled techniques for semi-supervised classification. In semi-supervised classification, both labeled and unlabeled …

We present the R package ssc that implements a collection of self-labeled techniques to construct a classification model. This family of techniques enlarges the original labeled set using the …

simpler single cell RNAseq data clustering (sscClust), is a package implement mutilple functionalities which are basic procedures in single cell RNAseq data analysis, including …

ssc. Provides a collection of self-labeled techniques for semi-supervised classification. In semi-supervised classification, both labeled and unlabeled data are used to train a classifier. This …

Self-training is a simple and effective semi-supervised learning classification method. The self-training classifier is initially trained with a reduced set of labeled examples. Then it is iteratively …

The San Sebastian Golden Stags and Lady Stags, also known collectively as the SSC-R Stags, are the National Collegiate Athletic Association (Philippines) varsity teams of the San …

Get started with the ssc package in R. Explore all available documentation, popular tutorials, and other key resources in this reference guide.

The ssc package offers a wrapper framework to train models from instances or directly from a precomputed distance or kernel matrix. The ssc package supports a generic interface for base …

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