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Linear Regression game: Difference between revisions

From Algolit

(Created page with " Linear Regression is one of the most well known and well understood algorithms in statistics and machine learning. It has been around for almost 200 years. It is an attrac...")
 
 
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    Linear Regression is one of the most well known and well understood algorithms in statistics and machine learning. It has been around for almost 200 years. It is an attractive model because the representation is so simple. In statistics, linear regression is is a statistical method that allows to summarize and study relationships between two continuous (quantitative) variables.
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by Algolit
  
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    The basis for this algorithm was invented by Francis Galton, a cousin of Charles Darwin and an accomplished 19th century scientist. He has often been criticized for his promotion of “eugenics” (planned breeding of humans). While studying the problem of heredity – understanding how strongly the characteristics of one generation of living things manifested in the following generation, he was the first to define the linear regression slope.
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[https://gitlab.constantvzw.org/algolit/mundaneum/tree/master/exhibition/6-Learners/Game_documentation Sources on Gitlab]
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Linear Regression is one of the best-known and best-understood algorithms in statistics and machine learning. It has been around for almost 200 years. It is an attractive model because the representation is so simple. In statistics, linear regression is a statistical method that allows to summarize and study relationships between two continuous (quantitative) variables.
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By playing this game you will realize that as a player you have a lot of decisions to make. You will experience what it means to create a coherent dataset, to decide what is in and what is not in. If all goes well, you will feel the urge to change your data in order to obtain better results. This is part of the art of approximation that is at the basis of all machine learning practices.
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Concept & realisation: An Mertens
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[[Category:Data_Workers]][[Category:Data_Workers_EN]]

Latest revision as of 18:21, 4 June 2019

by Algolit

Sources on Gitlab

Linear Regression is one of the best-known and best-understood algorithms in statistics and machine learning. It has been around for almost 200 years. It is an attractive model because the representation is so simple. In statistics, linear regression is a statistical method that allows to summarize and study relationships between two continuous (quantitative) variables.

By playing this game you will realize that as a player you have a lot of decisions to make. You will experience what it means to create a coherent dataset, to decide what is in and what is not in. If all goes well, you will feel the urge to change your data in order to obtain better results. This is part of the art of approximation that is at the basis of all machine learning practices.

Concept & realisation: An Mertens

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