random learning

In the field of machine learning, random forest is an important and common method of data mining.

在机器学习领域，随机森林是一种重要和常见的数据挖掘方法。

互联网摘选

And will describe a real-time body parts recognition algorithm which is based on self-made depth image sample library, local gradient feature extraction and combined with random forest learning.

本文主要讨论利用深度图像进行人体部位识别的问题，将阐述一种利用自制的深度图像样本库，提取局域梯度特征，结合随机森林学习的实时人体部位识别算法。

互联网摘选

This paper elaborates on the low learning efficiency in reinforcement learning due to improper generalization and random exploration policy under deterministic MDPS and proposes a hierarchical reinforcement learning algorithm based on system model.

针对强化学习算法的状态值泛化和随机探索策略在确定性MDP系统控制中存在着学习效率低的问题，本文提出基于模型的层次化强化学习算法。

互联网摘选

Random neural network ( RNN) is a special kind of artificial neural network, which is developed recently and has its own peculiarities on the structure, the learning algorithm, the state-updating rule and the applications.

随机神经网络（RNN）在人工神经网络中是一类比较独特、出现较晚的神经网络，它的网络结构、学习算法、状态更新规则以及应用等方面都因此具有自身的特点。

互联网摘选

A new ensemble-learning algorithm-Random Forest is applied in this paper. As a consequence, the selected index system is more objective and more suitable for machine learning.

本文引进组合学习算法的新方法随机森林（Random Forest，RF）来选择指标，使得到的指标体系更加客观，更加符合机器学习的特点。

互联网摘选

Research on Complete Random Learning Scheme in Ensemble Learning

集成学习中完全随机学习策略研究

互联网摘选

Research on the Part-of-Speech Tagging Method& POS Tagging using Conditional Random Fields and Transformation Based Learning

词性标注的方法研究&结合条件随机场和基于转换学习的方法进行词性标注

互联网摘选

Inspired by the theory of simple random walk, we propose a unified framework for semi-supervised learning, i.e. multilevel random walk ( MRW). MRW can produce numerous multi-class label propagation algorithms by constructing various component random walk models based on prior knowledge.

在简单随机游走理论的启发下，我们提出一个统一的半监督学习框架&多层随机游走，通过构建各种组件级的随机游走模型，可以产生一系列对应的多分类标签传播算法。

互联网摘选

The experimental evaluations show that the proposed asymmetric semi-supervised learning methodology in conjunction with random subspace theory is effective to improve CBIR performance and achieves better performance than some existing approaches.

实验结果表明，不对称的半监督学习策略及随机子空间理论可有效地改进SVM反馈性能，且所提出算法明显优于同类SVM反馈方法。

互联网摘选

the key theorem of rough random learning theory is given and proved;

给出并证明了基于粗糙随机样本的学习理论的关键定理；

互联网摘选

Skydiving, talking to that random stranger, learning a foreign language, picking a strange new book, taking Argentinian tango classes, rock climbing, learning how to sew... What new things will you try today?

跳伞、随便跟一个陌生人讲话、学一种外语、挑一本没看过的新书、上阿根廷探戈的课、攀岩、学习缝纫…今天你要挑战哪项新事物呢？

互联网摘选