Ensemble methods for machine learning
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Machine Learning
Machine Learning brings together all the state-of-the-art methods for making sense of data. With hundreds of worked examples and explanatory figures,
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Mathematics for Machine Learning
This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum o
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Mathematics for Machine Learning
This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum o
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Machine Learning for Hackers
Now that storage and collection technologies are cheaper and more precise, methods for extracting relevant information from large datasets is within t
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Computational Methods for Deep Learning
Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively
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Statistics and Machine Learning Methods for EHR Data
The book carefully evaluates and compares the standard statistical models and approaches with those of machine learning and deep learning methods and
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Statistics and Machine Learning Methods for EHR Data
The book carefully evaluates and compares the standard statistical models and approaches with those of machine learning and deep learning methods and
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Recent Methods from Statistics and Machine Learning for Credit Scoring
Credit scoring models are the basis for financial institutions like retail and consumer credit banks. The purpose of the models is to evaluate the likelihood of credit applicants defaulting in order to decide whether to grant them credit. The area under the receiver operating characteristic (ROC) curve (AUC) is one of the most commonly used measures to evaluate predictive...
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Machine Learning Toolbox for Social Scientists
Machine Learning Toolbox for Social Scientists covers predictive methods with complementary statistical "tools" that make it mostly self-contained. Th
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Handbook of Matching and Weighting Adjustments for Causal Inference Taylor & Francis Ltd
This handbook provides a comprehensive survey of the most recent methods of adjustment by matching, weighting, machine learning and their combinations. When used alone, matching and weighting do not use outcome information, so they are part of the design of an observational study. When used in conjunction with models for the outcome, matching and weighting may enhance the...
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Big Data
Big Data and methods for analyzing large data sets such as machine learning have deeply transformed scientific practice in many fields. This Element d
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