Лекции по Data Mining от Массачусетского технологического института

суббота, 7 ноября 2009, Александр Краковецкий

18 лекций по Data Mining от Массачусетского технологического института в pdf формате (на английском).

Content:

  • Data Mining Overview
  • Prediction and Classification with k-Nearest Neighbors
  • Example 1: Riding Mowers
  • Classification and Bayes Rule, Naïve Bayes
  • Classification Trees
  • Discriminant Analysis Example 2: Fisher's Iris data
  • Logistic Regression Case
  • Handlooms
  • Neural Nets
  • Discussion of homework - see Problem 1 in assignments section
  • Multiple Regression Review
  • Multiple Linear Regression in Data Mining
  • Regression Trees, Case: IBM/GM weekly returns
  • k-Means Clustering, Hierarchical Clustering
  • Principal Components 
  • Association Rules (Market Basket Analysis)

Страница курсов: http://ocw.mit.edu/OcwWeb/Sloan-School-of-Management/15-062Data-MiningSpring2003/LectureNotes/index.htm

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Data mining Portable Document Format Content (media) Classification (machine learning) K-nearest neighbor algorithm Bayes' theorem Decision tree Linear discriminant analysis Logistic regression Neural network Homework Linear regression Review K-means clustering Hierarchical clustering Principal component analysis Association rule learning Sloan Digital Sky Survey School

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