Matrix Factorization with Interval-Valued Data

Exploratory data analysis of interval-valued symbolic data with matrix visualization

Symbolic data analysis (SDA) has gained popularity over the past few years because of its potential for handling data having a dependent and hierarchical nature. Amongst many methods for analyzing SDA data, exploratory data analysis (EDA: Tukey, (1977)) with graphical presentation is an important one. Recent developments of graphical and visualization tools for SDA include zoom star, closed sha...

Symbolic Clustering with Interval-Valued Data

Interval-valued Fuzzy Soft Matrix Theory

An interval-valued programming approach to matrix games with payoffs of triangular intuitionistic fuzzy numbers

The purpose of this paper is to develop a methodology for solving a new type of matrix games in which payoffs are expressed with triangular intuitionistic fuzzy numbers (TIFNs). In this methodology, the concept of solutions for matrix games with payoffs of TIFNs is introduced. A pair of auxiliary intuitionistic fuzzy programming models for players are established to determine optimal strategies...

Maximum Margin Matrix Factorization with Netflix Data

Maximum Margin Matrix Factorization (MMMF), a collaborative filtering method, was recently introduced in [7] followed by an iterative solution presented in [6]. In this paper we analyze the performance of MMMF on a subset of the Netflix data based on RMSE and classification rate. We also present several modifications to improve the performance of the algorithm on the Netflix problem.