"learning threshold" is a correct and usable phrase in written English.
It typically refers to a point or range of difficulty that someone can handle in the process of learning something new. For example, "He had a low learning threshold and was able to pick up new skills quickly."
Thus, there is emerging evidence that virtual laboratory environments are useful for learning threshold concepts.
with is a learning threshold.
The low-cost, easy availability and development environments that have a low learning threshold makes system-on-chip (SoC) microcontrollers (μC) attractive for this task.
The main parameters of distance weighting factor, width, incremental learning threshold, number of BP hidden neurons, and momentum constant in ILRBF-BP are set as T = 1, σ = 3, δ = 0.01, M = 5, and α = 0, respectively.
Redish and Wilson (1993), Soloway (1993), and Kafai et al. (1997) also demonstrated that reorganizing scientific and mathematical concepts around computational mechanisms lowered the learning threshold, especially in domains like physics and biology.
For the VC problem, the sample distribution values of each dimension are between −1 and +1, and the main parameters of distance weighting factor, width, incremental learning threshold, number of BP hidden neurons, and momentum constant in ILRBF-BP are set as T = 1, σ = 0.4, δ = 0.001, M = 9, and α = 0.1, respectively.
While evaluating and comprehension are not synonymous, the ability to evaluate content should establish machine-learning threshold benchmarks for human behavior and intent.
One potential solution to this would be to develop a metacognition mechanism for learning these thresholds for a given dataset.
Instead of choosing an arbitrary score threshold, a threshold learning mechanism based on criteria such as coherence of GO term could be incorporated, or an edge-weighted network may be used.
For example, if one is looking for extreme events, one might look at the processing descriptions to learn what threshold values were used to determine out-of-range data and whether these data were removed or replaced.
Using a training phase is always a good method to learn the threshold.
