Company Filing History:
Years Active: 2007-2011
Title: **Innovations by Christopher N. Eichelberger**
Introduction
Christopher N. Eichelberger, based in Charlotte, NC, has made significant contributions to the field of data classification and prediction. With a total of two patents to his name, he showcases an innovative approach using mathematical models to enhance data processing efficiency and accuracy. Eichelberger's work primarily focuses on incremental clustering methods, paving the way for advancements in data analysis.
Latest Patents
Eichelberger’s latest invention, the "Incremental Clustering Classifier and Predictor," introduces mathematical model-based methods for classifying sets of data and predicting new data values. This invention is grounded in the concepts of similarity and cohesion. To enhance processing efficiency, the methods incorporate weighted attribute relevance, which aids in constructing unbiased classification trees. Additionally, sum pairing is utilized to reduce the number of nodes accessed during classification or prediction operations.
To bolster prediction accuracy, the invention employs weighted voting on target attribute values to create a prediction profile. Notably, it also empowers operators to identify the importance of attributes, allowing them to reconstruct classification trees by omitting attributes deemed unimportant, thereby further enhancing the efficiency of node processing in classification structures. The invention includes a graphical user interface that permits operators to modify instance attribute values, enabling exploration of classified data sets while visually contrasting members based on distinguishing features.
Career Highlights
Christopher N. Eichelberger is currently affiliated with the University of North Carolina at Charlotte. His academic environment fosters innovation and collaboration, allowing him to work on cutting-edge research projects that push the boundaries of data science.
Collaborations
In his endeavors, Eichelberger collaborates with notable colleagues, including Mirsad Hadzikadic and Benjamin F. Bohren. Together, they contribute to the advancement of knowledge in their respective fields, combining their expertise to enrich research outcomes.
Conclusion
Christopher N. Eichelberger stands out as a prominent inventor in the realm of data classification and prediction. His innovative strategies, particularly in incremental clustering methods, exemplify the potential of mathematics in addressing complex data challenges. As he continues to develop groundbreaking inventions, his work remains a valuable asset to both the academic community and the broader field of data science.