A bias correction for the minimum error rate in cross-validation

A bias correction for the minimum error rate in cross-validation

Tuning parameters in supervised learning problems are often estimated by cross-validation. The minimum value of the cross-validation error can be biased downward as an estimate of the test error at that same value of the tuning parameter. We propose a simple method for the estimation of this bias that uses information from the crossvalidation process. As a result, it requires essentially no add...

A Bias Correction for the Minimum Error Rate in Cross-validation By

Tuning parameters in supervised learning problems are often estimated by cross-validation. The minimum value of the cross-validation error can be biased downward as an estimate of the test error at that same value of the tuning parameter. We propose a simple method for the estimation of this bias that uses information from the cross-validation process. As a result, it requires essentially no ad...

Minimum Distance Error Correction

A method is presented for incorporating error correction using a minimum distance measure into LR parsers. The method is suitable for use by an automatic parser-generator. State information in the LR parser stack at the point of detection of error is used to generate a set of strings which are potential repairs to the input. A string with least minimum distance from the actual input is chosen a...

the effects of error correction methods on pronunciation accuracy

هدف از انجام این تحقیق مشخص کردن موثرترین متد اصلاح خطا بر روی دقت آهنگ و تاکید تلفظ کلمه در زبان انگلیسی بود. این تحقیق با پیاده کردن چهار متد ارائه اصلاح خطا در چهار گروه، سه گروه آزمایشی و یک گروه تحت کنترل، انجام شد که گروه های فوق الذکر شامل دانشجویان سطح بالای متوسط کتاب اول passages بودند. گروه اول شامل 15، دوم 14، سوم 15 و آخرین 16 دانشجو بودند. دوره مربوطه به مدت 10 هفته ادامه یافت و د...

Error rate estimation via cross-validation and learning curve theory