This is a Matlab project from my early days as a Computer Science student
This programm was created for the fifth semester class Pattern Recognision and it is the final project necessary to pass the class
A Matlab script that applies the basic sequential clustering to evaluate the number of user groups by using the hierarchical clustering and k-means algorithms. Using the k-means fold the classifiers that are a neural network and the other least squares to evaluate them.
- Apply the basic sequential schema to estimate the number of user groups according to their preferences.
- Based on the estimation of Step 1, apply the k-means algorithm and the hierarchical clustering algorithm.
- Using the 5-fold format provided, design, implement, and evaluate two classifiers, which solve the following problem: if a user and a movie is given, the classifier decides whether the user saw the movie (class 1) or not (class 2) . One classifier will be a neural network and the other a least squares.
- The MovieLens dataset used for 100k ratings https://grouplens.org/datasets/movielens/100k/
- This program was written in Matlab IDE
- This repository was created to show the variety of the work I did and experience I gained as a student