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Confidence intervals on recall and eRecall

There is an ongoing discussion about methods of estimating the recall of a production, as well as estimating a confidence interval on that recall. One approach is to use the control set sample, drawn at the start of production to estimate collection richness and guide the predictive coding process, to also estimate the final confidence […] → Read More: Confidence intervals on recall and eRecall

Confidence intervals on recall and eRecall

There is an ongoing discussion about methods of estimating the recall of a production, as well as estimating a confidence interval on that recall. One approach is to use the control set sample, drawn at the start of production to estimate collection richness and guide the predictive coding process, to also estimate the final confidence […] → Read More: Confidence intervals on recall and eRecall

Confidence intervals on recall and eRecall

There is an ongoing discussion about methods of estimating the recall of a production, as well as estimating a confidence interval on that recall. One approach is to use the control set sample, drawn at the start of production to estimate collection richness and guide the predictive coding process, to also estimate the final confidence […] → Read More: Confidence intervals on recall and eRecall

Confidence intervals on recall and eRecall

There is an ongoing discussion about methods of estimating the recall of a production, as well as estimating a confidence interval on that recall. One approach is to use the control set sample, drawn at the start of production to estimate collection richness and guide the predictive coding process, to also estimate the final confidence […] → Read More: Confidence intervals on recall and eRecall

Confidence intervals on recall and eRecall

There is an ongoing discussion about methods of estimating the recall of a production, as well as estimating a confidence interval on that recall. One approach is to use the control set sample, drawn at the start of production to estimate collection richness and guide the predictive coding process, to also estimate the final confidence […] → Read More: Confidence intervals on recall and eRecall

Confidence intervals on recall and eRecall

There is an ongoing discussion about methods of estimating the recall of a production, as well as estimating a confidence interval on that recall. One approach is to use the control set sample, drawn at the start of production to estimate collection richness and guide the predictive coding process, to also estimate the final confidence […] → Read More: Confidence intervals on recall and eRecall

Why training and review (partly) break control sets

A technology-assisted review (TAR) process frequently begins with the creation of a control set—a set of documents randomly sampled from the collection, and coded by a human expert for relevance. The control set can then be used to estimate the richness (proportion relevant) of the collection, and also to gauge the effectiveness of a predictive […] → Read More: Why training and review (partly) break control sets

Why training and review (partly) break control sets

A technology-assisted review (TAR) process frequently begins with the creation of a control set—a set of documents randomly sampled from the collection, and coded by a human expert for relevance. The control set can then be used to estimate the richness (proportion relevant) of the collection, and also to gauge the effectiveness of a predictive […] → Read More: Why training and review (partly) break control sets

Why training and review (partly) break control sets

A technology-assisted review (TAR) process frequently begins with the creation of a control set—a set of documents randomly sampled from the collection, and coded by a human expert for relevance. The control set can then be used to estimate the richness (proportion relevant) of the collection, and also to gauge the effectiveness of a predictive […] → Read More: Why training and review (partly) break control sets

Why training and review (partly) break control sets

A technology-assisted review (TAR) process frequently begins with the creation of a control set—a set of documents randomly sampled from the collection, and coded by a human expert for relevance. The control set can then be used to estimate the richness (proportion relevant) of the collection, and also to gauge the effectiveness of a predictive […] → Read More: Why training and review (partly) break control sets