maximum mini-batch iteration count (default 100,000)
default patience count (default 5,000)
multiplier for calculating patience (default x2)
threshold that iteration is marked as "improved" (default 95% = 0.95)
maximum-tolerant loss value. (default 0.0001)
step count for validation (default 100)
threshold that iteration is marked as "improved" (default 95% = 0.95)
maximum-tolerant loss value.
maximum-tolerant loss value. (default 0.0001)
maximum mini-batch iteration count (default 100,000)
default patience count (default 5,000)
multiplier for calculating patience (default x2)
step count for validation (default 100)
Criteria: When to stop training
This case class defines when to stop training. Training stops if one of the following condition is satisfied.
max(patience, bestIteration * patienceStep)
Validation is done for each
validationFreq
iterations, and whenever current/best loss ratio below improveThreshold, that iteration is marked as best iteration.maximum mini-batch iteration count
(default 100,000)
default patience count
(default 5,000)
multiplier for calculating patience
(default x2)
threshold that iteration is marked as "improved"
(default 95% = 0.95)
maximum-tolerant loss value.
(default 0.0001)
step count for validation
(default 100)