A Neural Network For Speedy Trial

Ray R. Hashemi, Therese M. Schafer, William G. Hinson, John R. Talburt

Research output: Contribution to journalArticlepeer-review

Abstract

In recent years, the case loads of judges have increased, while speedy trial laws place a time limit between the defendant's arrest and trial dates. Because of this time constraint, it seems that for minor cases, judges pass sentences based on a set of certain factors (patterns) not based on the individual merits of each case. Patterns may be learned by a neural network. In this paper, we investigate the credibility of the neural network approach as a viable tool in the sentencing process and we show its superiority over the ID3 approach.
Original languageAmerican English
JournalThe ACM SIGICE Bulletin
Volume22
StatePublished - Oct 1996

Disciplines

  • Engineering
  • Computer Sciences

Keywords

  • Neural network
  • Speedy trial

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