What Is Statistical Learning In Machine Learning
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What Is Statistical Learning In Machine Learning
Statistical learning theory is the broad framework for studying the concept of inference in both supervised and unsupervised machine learning Inference covers the entire spectrum of machine learning from gaining knowledge making predictions or decisions and constructing models from a set of labeled or unlabeled data How to train predictive models and analyze machine learning results. An overview of machine learning deep learning and reinforcementFrontiers common statistical concepts in the supervised machine.
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Statistics is the mathematical study of data Using statistics an interpretable statistical model is created to describe the data and this model can then be used to infer something about the data or even to predict values that are not present in the sample data used to create the model The accuracy of prediction is not the focus of statistics Statistics is a collection of tools that you can use to get answers to important questions about data. You can use descriptive statistical methods to transform raw observations into information that you can understand and share. You can use inferential statistical methods to reason from small samples of data to whole domains.
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What Is Statistical Learning In Machine LearningStatistical learning theory is a framework for machine learning that draws from statistics and functional analysis. It deals with finding a predictive function based on the data presented.... Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis 1 2 3 Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data
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