Jersey City, NJ, United States of America

Yubo Cheng

This inventor holds 1 USPTO granted patent. Top assignee: Mitsubishi Electric Research Laboratories, Inc.. Active years: 2013.


Average Co-Inventor Count = 2.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2013

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1 patent (USPTO):Explore Patents

Title: Yubo Cheng: Innovator in Regression Analysis

Introduction

Yubo Cheng is a prominent inventor based in Jersey City, NJ (US). He has made significant contributions to the field of regression analysis through his innovative methods. His work focuses on enhancing the selection of features used in continuous-valued regression analysis.

Latest Patents

Yubo Cheng holds a patent for a "Method for selecting features used in continuous-valued regression analysis." This method involves selecting features based on training data that includes features and corresponding continuous target values. The process includes thresholding and discretizing target values to produce discrete target values. Subsequently, categorical feature selection is applied to identify the most relevant features for regression analysis. This innovative approach can significantly improve the accuracy and efficiency of regression models.

Career Highlights

Yubo Cheng is currently employed at Mitsubishi Electric Research Laboratories, Inc. His role at this esteemed organization allows him to further his research and development in advanced analytical methods. His expertise in regression analysis has positioned him as a valuable asset in the field.

Collaborations

Yubo Cheng collaborates with various professionals in his field, including his coworker Kevin William Wilson. Their combined efforts contribute to the advancement of innovative solutions in regression analysis.

Conclusion

Yubo Cheng's contributions to the field of regression analysis through his patented methods demonstrate his commitment to innovation and excellence. His work continues to influence the way features are selected in continuous-valued regression analysis, paving the way for more accurate predictive models.

Profile summary based on public USPTO records.
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