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