gradient boosting造句

例句与造句

1. The gradient boosting solution starts with the observation that a perfect would imply
2. The first Honourable Mention went to Dell Zang ( team zeditor ) who used a machine learning technique called gradient boosting.
3. Like other boosting methods, gradient boosting combines weak " learners " into a single strong learner, in an iterative fashion.
4. So, gradient boosting is a gradient descent algorithm; and generalizing it entails " plugging in " a different loss and its gradient.
5. One natural regularization parameter is the number of gradient boosting iterations " M " ( i . e . the number of trees in the model when the base learner is a decision tree ).
6. It's difficult to find gradient boosting in a sentence. 用gradient boosting造句挺难的
7. In November 2009 a Russian search engine Yandex announced that it had significantly increased its search quality due to deployment of a new proprietary MatrixNet algorithm, a variant of gradient boosting method which uses oblivious decision trees.
8. At each stage 1 \ le m \ le M of gradient boosting, it may be assumed that there is some imperfect model F _ m ( at the outset, a very weak model that just predicts the mean in the training set could be used ).
9. Gradient boosting method assumes a real-valued " y " and seeks an approximation \ hat { F } ( x ) in the form of a weighted sum of functions h _ i ( x ) from some class !, called base ( or weak ) learners:
10. Skytree has machine learning methods that include : random decision forests, kernel density estimation, K-means, singular value decomposition, gradient boosting, decision tree, 2-point correlation, range searching, K-nearest neighbors algorithm, linear regression, support vector machine, and logistic regression.
11. "' TWANG "', the Toolkit for Weighting and Analysis of Nonequivalent Groups, developed by the statistics group of the RAND Corporation, contains a set of functions to support Rubin causal modeling of observational data through the estimation and evaluation of propensity score weights by applying gradient boosting.
12. The gradient boosting algorithm does not change F _ m in any way; instead, it improves on it by constructing a new model that adds an estimator to provide a better model F _ { m + 1 } ( x ) = F _ m ( x ) + h ( x ).