World's Best Scientists 2026 revealed!

Overview

Sholom M. Weiss is affiliated with Rutgers, The State University of New Jersey in the United States. Their academic profile prominently identifies them with this institution, indicating active engagement in research and teaching within this academic environment.

The researcher has not documented recent papers or specific publications available for review. There are no listed frequent co-authors or collaborative networks, which suggests either an individual research focus or that collaborations are not publicly detailed.

Details regarding main fields of study, subfields, and specific research topics are not provided. Similarly, information on frequent publication venues and book publications is unavailable, limiting insight into the breadth or specialization of their scholarly output.

No records of awards or distinctions are noted in the available data, and there are no indications of the researcher being deceased.

Best Publications

  • Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems

    Sholom M. Weiss;Casimir A. Kulikowski

  • Automated learning of decision rules for text categorization

    Chidanand Apté;Fred Damerau;Sholom M. Weiss

  • Text Mining: Predictive Methods for Analyzing Unstructured Information

    Sholom M. Weiss;Nitin Indurkhya;Tong Zhang;Fred Damerau

  • Predictive Data Mining: A Practical Guide

    Sholom M. Weiss;Nitin Indurkhya

  • A model-based method for computer-aided medical decision-making

    Sholom M. Weiss;Casimir A. Kulikowski;Saul Amarel;Aran Safir

  • An empirical comparison of pattern recognition, neural nets, and machine learning classification methods

    Sholom M. Weiss;Ioannis Kapouleas

  • A Practical Guide to Designing Expert Systems

    Sholom M. Weiss;Casimir A. Kulikowski

  • Data mining with decision trees and decision rules

    Chidanand Apté;Sholom Weiss

  • Fundamentals of Predictive Text Mining

    Sholom M. Weiss;Nitin Indurkhya;Tong Zhang

  • EXPERT: a system for developing consultation models

    Sholom M. Weiss;Casimir A. Kulikowski

  • Towards language independent automated learning of text categorization models

    Chidanand Apté;Fred Damerau;Sholom M. Weiss

  • Rule-based machine learning methods for functional prediction

    Sholom M. Weiss;Nitin Indurkhya

  • Representation of Expert Knowledge for Consultation: The CASNET and EXPERT Projects

    Casimir A. Kulikowski;Sholom M. Weiss

  • Predictive algorithms in the management of computer systems

    R. Vilalta;C. V. Apte;J. L. Hellerstein;S. Ma

  • Automatic knowledge base refinement for classification systems

    Allen Ginsberg;Sholom M. Weiss;Peter Politakis

  • Maximizing the predictive value of production rules

    S. M. Weiss;R. S. Galen;P. V. Tadepalli

  • SEEK2: a generalized approach to automatic knowledge base refinement

    Allen Ginsberg;Sholom Weiss;Peter Politakis

  • Reduced complexity rule induction

    Sholom M. Weiss;Nitin Indurkhya

  • Small sample error rate estimation for k-NN classifiers

    S.M. Weiss

  • Developing microprocessor based expert models for instrument interpretation

    Sholom M. Weiss;Casimir A. Kulikowski;Robert S. Galen

Frequent Co-Authors

Tong Zhang
Tong Zhang University of Illinois at Urbana-Champaign
Prasad Tadepalli
Prasad Tadepalli Oregon State University

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