Journal of Investment, Banking and Finance(JIBF)

Denison University, USA

Publications

• Research Article   
  Algorithms for Estimating Linear Function in Data Mining
  Author(s): Thomas Hoang*
  
  The main goal of this topic is to showcase several studied algorithms for estimating the linear utility function to predict the users’ preferences. For example, if a user comes to buy a car that has several attributes including speed, color, age, etc in a linear function, the algorithms that we present in this paper help with estimating this linear function to filter out a small subset that would be of best interest to the user among a million tuples in a very large database. In addition, the estimating linear function could also be applicable in getting to know what the data can do or predicting the future based on the data that is used in data science, which is demonstrated by the GNN, PLOD algorithms [1,2]. In the ever-evolving field of data science, deriving valuable insights from large datasets is critical for informed decision-making, particularly in predictive application.. Read More»
  

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