Laboratorium 11 - Systemy rekomendacyjne i detekcja anomalii

Ćwiczenia bazujące na materiałach Andrew Ng.
Przed zajęciami przejrzyj wykłady XV-XVI: Anomaly detection and recommender systems

Instructions in English.

Ćwiczenia do pobrania (files to download): anomaly-detection.zip

Lista i opis plików

Pliki oznaczone znakiem wykrzyknika (:!:) należy wypełnić własnym kodem

  • ex8.m - Octave/Matlab script for first part of exercise
  • ex8_cofi.m - Octave/Matlab script for second part of exercise
  • ex8data1.mat - First example Dataset for anomaly detection
  • ex8data2.mat - Second example Dataset for anomaly detection
  • ex8_movies.mat - Movie Review Dataset
  • ex8_movieParams.mat - Parameters provided for debugging
  • multivariateGaussian.m - Computes the probability density function for a Gaussian distribution
  • visualizeFit.m - 2D plot of a Gaussian distribution and a dataset
  • checkCostFunction.m - Gradient checking for collaborative filtering
  • computeNumericalGradient.m - Numerically compute gradients
  • fmincg.m - Function minimization routine (similar to fminunc)
  • loadMovieList.m - Loads the list of movies into a cell-array
  • movie_ids.txt - List of movies
  • normalizeRatings.m - Mean normalization for collaborative filtering
  • :!: estimateGaussian.m - Estimate the parameters of a Gaussian distribution with a diagonal covariance matrix
  • :!: selectThreshold.m - Find a threshold for anomaly detection
  • :!: cofiCostFunc.m - Implement the cost function for collaborative filtering
pl/dydaktyka/ml/lab11.txt · ostatnio zmienione: 2019/06/27 15:50 (edycja zewnętrzna)
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