Sentence examples for categorization error from inspiring English sources

When the total fixation time in the contact zone was equal to or exceeded 1000 ms, the error was probably due to a failure to categorize the situation according to the Laws of the Game (categorization error).

Errors could thus occur at two levels of the decision-making process: 1) a perception error if the referee failed to focus for a significant amount of time (1000 ms) in the contact zones; 2) a categorization error if the contact zone was perceived thoroughly but the referee failed to categorize the situation correctly.

We did not simulate any categorization error.

Simulations of categorization error have consistently shown that correlation between true values and scale scores increase with the number of response options [ 12].

A defining feature of the Deep Dream algorithm is the use of backpropagation to alter the input image in order to minimize categorization errors.

The Deep Dream algorithm also uses error backpropagation, but instead of updating the weights between nodes in the DCNN, it fixes the weights between nodes across the entire network and then iteratively updates the input image itself to minimize categorization errors via gradient descent.

(We understand that companies and categories may at times overlap and there may be categorization errors. This list is not exhaustive, and there are undoubtedly companies we did not identify.

Although one can argue that the criterion of 1000 ms is arbitrary, we believe this to be a reasonable estimate of the proportion of categorization errors, showing that it is important to encode and give meaning to the perceived stimulus according to the Laws of the Game.

However, she is willing to make more categorization errors per second delay than subject 5.

In our model, categorization errors arise when incorrect prior predictions coincide with high delay costs (see equations 11 and 12).

In this work, we have chosen to focus on modelling reaction time data and have deliberately ignored categorization errors.