Impact of Data Preprocessing on Integrative Matrix Factorization of Single Cell Data
نویسندگان
چکیده
منابع مشابه
Sparse and unique nonnegative matrix factorization through data preprocessing
Nonnegative matrix factorization (NMF) has become a very popular technique in machine learning because it automatically extracts meaningful features through a sparse and part-based representation. However, NMF has the drawback of being highly ill-posed, that is, there typically exist many different but equivalent factorizations. In this paper, we introduce a completely new way to obtaining more...
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ژورنال
عنوان ژورنال: Frontiers in Oncology
سال: 2020
ISSN: 2234-943X
DOI: 10.3389/fonc.2020.00973