Scientific Research Publishing

Read full paper at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=52267#.VI-sxcnQrzE Author(s) Sergio Pissanetzky Affiliation(s) School of Science and Computer Engineering, University of Houston, Clear Lake, Texas, USA . ABSTRACT The big problem of Big Data is the lack of a machine learning process that scales and finds meaningful features. Humans fill in for the insufficient automation, but the complexity of the tasks outpaces the human mind’s capacity to comprehend the data. Heuristic partition methods may help but still need humans to adjust the parameters. The same problems exist in many other disciplines and technologies that depend on Big Data or Machine Learning. Proposed here is a frac...

Read full paper at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=52267#.VI5IJcnQrzE \ Author(s) Sergio Pissanetzky Affiliation(s) School of Science and Computer Engineering, University of Houston, Clear Lake, Texas, USA . ABSTRACT The big problem of Big Data is the lack of a machine learning process that scales and finds meaningful features. Humans fill in for the insufficient automation, but the complexity of the tasks outpaces the human mind’s capacity to comprehend the data. Heuristic partition methods may help but still need humans to adjust the parameters. The same problems exist in many other disciplines and technologies that depend on Big Data or Machine Learning. Proposed here is a fr...