Sentence examples for over-optimized from inspiring English sources

Furthermore, when selecting cut-points the method is often not specified, or the "optimal" cut-point method is used, leading to over-optimized and irreproducible estimates.

From over-optimized GPS sending unwitting tourists into barely existent dirt paths inside Death Valley to Microsoft's AI Twitter bot going rogue after Twitter pranksters filled its brain with hate speech; whether unintentional or by malicious design, algorithms behaving unexpectedly are now a fact of life.

The predictive performances of AlgPred (MCC = 0.201) and DASARP (MCC = 0.298) are low, suggesting that these systems may be over-optimized for positive prediction.

Considering that all samples were used to generate the model, the estimated accuracy of the gene profile could be over-optimized.

These results suggested that the models developed in this study are not over-optimized.

However, as this minimal set was possibly over-optimized to fit exactly those sets that were used for its composition, this set might not perform well in a newly identified cohort from a different geographic region.

In addition, the effect of operational conditions was studied over optimized sample.

A dynamic programming based approach is presented which yields up to three times improvement in efficiency over optimized open loop designs and 35% better efficiency over reported closed loop strategies that focus on optimizing velocities.

Compared to the EOP predictions with fixed base data intervals, the "predictions over optimized data intervals" performs better for the prediction of UT1-UTC, and shows a significant improvement for the prediction of polar motion, and particularly promotes our competitive level in the international activity of Earth Orientation Parameters Combination of Prediction Pilot Project.

This study firstly employs the calculation of base sequence with different length, in 1 90 day predictions of EOP (the UT1-UTC and polar motion), by the combined method of least squares and autoregressive model, and find the base sequence with best result for different prediction spans, which we call as "predictions over optimized data intervals".

Spaced-repetition, a learning approach that focuses on reviewing content multiple times over optimized time intervals is one of the most effective ways to improve long-term retention [ 14- 18].