http://www-bcf.usc.edu/~gareth/ISL/
An Overview of Statistical Learning
Statistical learning refers to a vast set of tools for understanding data .These tools can be classified as supervised or unsupervised. Broadly speaking, supervised statistical learning involves building a statistical model for pre-dicting, or estimating, an output based on one or more inputs. Problems of this nature occur in fields as diverse as business, medicine, astrophysics, and public policy. With unsupervised statistical learning, there are inputs but no supervising output; nevertheless we can learn relationships and struc-ture from such data. To provide an illustration of some applications of statistical learning, we briefly discuss three real-world data sets that are considered in this book.
An Overview of Statistical Learning
Statistical learning refers to a vast set of tools for understanding data .These tools can be classified as supervised or unsupervised. Broadly speaking, supervised statistical learning involves building a statistical model for pre-dicting, or estimating, an output based on one or more inputs. Problems of this nature occur in fields as diverse as business, medicine, astrophysics, and public policy. With unsupervised statistical learning, there are inputs but no supervising output; nevertheless we can learn relationships and struc-ture from such data. To provide an illustration of some applications of statistical learning, we briefly discuss three real-world data sets that are considered in this book.