Rating

    No results.
12

Finite population protocols and selection training methods

In a previous post, I compared three methods of selecting training examples for predictive coding—random, uncertainty and relevance. The methods were compared on their efficiency in improving the accuracy of a text classifier; that is, the number of training documents required to achieve a certain level of accuracy (or, conversely, the level of accuracy achieved […] → Read More: Finite population protocols and selection training methods

Finite population protocols and selection training methods

In a previous post, I compared three methods of selecting training examples for predictive coding—random, uncertainty and relevance. The methods were compared on their efficiency in improving the accuracy of a text classifier; that is, the number of training documents required to achieve a certain level of accuracy (or, conversely, the level of accuracy achieved […] → Read More: Finite population protocols and selection training methods

Finite population protocols and selection training methods

In a previous post, I compared three methods of selecting training examples for predictive coding—random, uncertainty and relevance. The methods were compared on their efficiency in improving the accuracy of a text classifier; that is, the number of training documents required to achieve a certain level of accuracy (or, conversely, the level of accuracy achieved […] → Read More: Finite population protocols and selection training methods

Finite population protocols and selection training methods

In a previous post, I compared three methods of selecting training examples for predictive coding—random, uncertainty and relevance. The methods were compared on their efficiency in improving the accuracy of a text classifier; that is, the number of training documents required to achieve a certain level of accuracy (or, conversely, the level of accuracy achieved […] → Read More: Finite population protocols and selection training methods

Finite population protocols and selection training methods

In a previous post, I compared three methods of selecting training examples for predictive coding—random, uncertainty and relevance. The methods were compared on their efficiency in improving the accuracy of a text classifier; that is, the number of training documents required to achieve a certain level of accuracy (or, conversely, the level of accuracy achieved […] → Read More: Finite population protocols and selection training methods

Gesture Viewport: Interacting with Media Content Using Finger Gestures on Any Surface

At ICME 2014 in Chengdu, China, we presented a technical demo called “Gesture Viewport,” which is a projector-camera system that enables finger gesture interactions with media content on any surface. In the demo, we used a portable Pico projector to project a viewport widget (along with its content) onto a desktop and a Logitech webcam […] → Read More: Gesture Viewport: Interacting with Media Content Using Finger Gestures on Any Surface

12