搜索资源列表
ELM-in-tumor-classification
- 提出了一种基于数据集分割的极限学习机集成算法——DS-E-ELM.-Extreme Learning Machine proposed integration algorithm DS-E-ELM dataset based segmentation.
dataset_611081
- 该数据为TSP测试库数据，可用做TSP算法的测试，目前大多tsp测试都选用这个库里的数据为实例，它来自标准的TSPLIB95库。-TSP is a dataset directory which contains some examples of data for the traveleing salesperson problem. Most of these examples come TSPLIB, a collection of traveling salesman problem
ArcEngine
- ArcEngine加载图层的五个步骤 1.创建一个类工厂 2.使用类工厂创建一个要使用的工作区 3.使用工作区打开并得到图层的dataset 4.把dataset装入到新建的图层实例 5.把图层加载到MapControl控件-ArcEngine load layers five steps 1. Create a class factory 2. Use the class factory to create a work area to be used 3.
Robust_Face_Landmark
- 在现实世界条件下获取人脸存在较大的变化在形状和遮挡由于不同在姿态、表情、附属品的使用，例如，太阳镜和帽子以及与目标体（e.g. 食物）的交。当前的人脸界标估计方法在这种条件下努力但由于缺乏一种有效的理论方法用于处理局外点。我们提供了一个新奇的方法，称为Robust Cascaded Pose Regression (RCPR)，通过检测显式的遮挡且使用鲁棒的形状索引的特征可以减少exposure对于局外点。我们证明RCPR改进先前的界标估计方法在3个通用的人脸数据集上(LFPW, LFW and
learning-to-detect-motion-boundaries
- We propose a learning-based approach for motion boundary detection. Precise localization of motion boundaries is essential for the success of optical fl ow estimation, as motion boundaries correspond to discontinuities of the optical fl ow
bayes_on_pima
- bayes classifier on pima dataset
Challenge_Data
- 故障预测与健康管理数据PHM，数据格式为txt，希望对有需要的同志有帮助。英文描述建议大家看看，说不定会有帮助。-5. PHM08 Challenge data set the data challenge competition held at the 1st international conference on Prognostics and Health Management (PHM08) is being made publicly available. The dataset i
2808-14159-1-PB
- In this paper, we systematically explore feature definition and selection strategies for sentiment polarity classification. We begin by exploring basic questions, such as whether to use stemming, term frequency versus binary weighting, negation-enr
Extend Yale B dataset
- 用于人脸聚类的图像数据集。可以用于人脸图像聚类，子空间聚类等一系列相关的应用。
nodes
- full dataset for all model learning
Iris-Dataset-Analysis-master
- 用决策树-回归分析模型来分析鸢尾花数据，训练后最终可以得到模型的准确率(Using decision tree-regression analysis model to analyze iris data, the accuracy of the model can be obtained after training.)