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An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data. The text begins with a revision of estimation and hypothesis testing methods, c...

Subjects / keywords: Computer science; Technological innovations; Machine learning; Artificial intelligence

Subjects / keywords: Neural networks (Computer science); Artificial intelligence; Information networks; Machine learning

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last 10 years, due to the increased availability of documents in digital form and the ensuing n...

Statistical procedures for missing data have vastly improved, yet misconception and unsound practice still abound. The authors frame the missing-data problem, review methods, offer advice, and raise issues that remain un...

Subjects / keywords: Classifier (UML); Gene; Computer science; Feature selection; Redundancy (engineering); Gene selection; Support vector machine; Computational biology; sort; Artificial intelligence; Pattern recognition (psychology); Data ...

Subjects / keywords: Gradient boosting; Parameterized complexity; Mathematics; Robustness (evolution); Boosting (machine learning); Regression; Mathematical optimization; Algorithm; Data point; Computer science; Statistics; Artificial intell...

We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, we find that standard machine learning tec...

Subjects / keywords: Regret; Dilemma; Reinforcement learning; Logarithm; Mathematical optimization; Computer science; Mathematical economics; Action (physics); Bounded function; Simple (philosophy); Mathematics; Artificial intelligence