Численные методы обучения по прецедентам (практика, В.В. Стрижов)/Примеры

Материал из MachineLearning.

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(Title: Indexation demo)
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*''Demo script:'' demo_indexation
*''Demo script:'' demo_indexation
[[Изображение:Demo indexation 01.png|400px]]
[[Изображение:Demo indexation 01.png|400px]]
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===Title: Least Squares Linear Fit===
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*''Folder:'' LeastSquares
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*''Description:'' It shows how to use minimal least squares method to fit data. See more detailed description at demo_least_squares_fit.html
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*''Demo script:'' demo_least_squares_fit
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[[Изображение:Demo least squares fit.png|300px]]

Версия 14:58, 6 июня 2013

Содержание

Title: Phosphor curve differences

  • Folder: CurveDifferences
  • Description: Phosphor curves 0-1 classification illustration. 0-class curve is blue coloured, 1-class curve is red coloured. See more detailed description at demo_curve_differences.html
  • Demo script: demo_curve_differences

Title: Classification using logistic regression

  • Folder: DataGenerationExample
  • Description: This demo shows how to compute a separation hyperplane to classify objects. The hyperplane separates one class of objects from another. See more detailed description at demoDataGen.html
  • Demo script: demoDataGen

Title: Generalized linear models example

  • Folder: GLM
  • Description: This demo shows how to deal with the different hypothesis on data generation. The data generation hypothesis here is an assumption about the link function. See more detailed description at demo_GLM.html
  • Demo script: demo_GLM

Title: Income vs Lifespan illustration

  • Folder: IncomeVsLifeSpan
  • Description: Demo illustrates dependence between income and lifespan by countries.
  • Demo script: IncomeVsLifespan


Title: Indexation demo

  • Folder: Indexation
  • Description: This demo shows how to use indices of sorted sets and how to recover the unsorted set from the sorted one. See more detailed description at demo_indexation.html
  • Demo script: demo_indexation

Title: Least Squares Linear Fit

  • Folder: LeastSquares
  • Description: It shows how to use minimal least squares method to fit data. See more detailed description at demo_least_squares_fit.html
  • Demo script: demo_least_squares_fit

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