Sentence examples for reverse classification from inspiring English sources

Recall measures the fraction of correctly labelled positive examples, precision describes the correctness of positive instances prediction, whereas MCC is a balanced measure of binary classification effectiveness, ranging from −1 to 1, where 1 corresponds to error-free class labelling and −1 to reverse classification [7, 35].

In this case, reversing the classification would yield a result superior to an average random prediction.

The surge in the number of New Zealand philosophers piqued the curiosity of PBRF reviewers who eventually reversed the classifications.

In contrast, reverse correlation, another classification image methods, promises to reveal the represented visual information, i.e. the visual information effective and ineffective that an observer relies upon to resolve a task [20] [22].

DESDE-LTC has followed a reverse sequence: this classification was preceded by the development of instruments for assessing mental health services (ESMS) [ 20], services for elders (DESDAE) [ 40] and services for persons with disabilities (DESDE) [ 3].

Her father fought for years in court and finally had the classification reversed, but was heartbroken when Laing eloped with a black man.

We introduce a new variant of the psychophysical reverse-correlation or classification image method to estimate and localize the physical features of the stimuli which correlate with the perceived brightness, using a brightness-matching task.

Anwar et al. describe a method for Ancient Coin Classification Using Reverse Motif Recognition for image-based classification of Roman Republican coins in 2015 [40].

It is likely that a spectrum of responses ranging from only symptom reduction to complete reverse remodeling exists and classification should preferably cover the broad spectrum of this response.

SVM modules are designed for forward or reverse fault identification and fault classification using single terminal data.

We use a new psychophysical reverse correlation method known as classification images [7] [9] that allows both localization and characterization of the stimulus information that correlates with perceived brightness.