Why Time Series Data Is Unique A time series is a series of data points indexed in time. The fact that time series data is ordered makes it unique in the data space because it often displays serial dependence序列依赖. Serial dependence occurs when the va…

3.1.7. Cross validation of time series data Time series data is characterised by the correlation between observations that are near in time (autocorrelation). However, classical cross-validation techniques such as KFold and ShuffleSplit assume the sa…

本文摘译自 Netflix TechBlog : Scaling Time Series Data Storage - Part I 重点:扩容.缓存.冷热分区.分块. 时序数据 - 会员观看历史 Netflix的用户,每天观看1.4亿小时的内容.每位用户在查看影片和保存观看记录的时候,都会提供几个数据点.Netflix分析这些观看数据并且提供实时的精确书签和个性化推荐. 观看历史数据在如下三个方面增长: 随着时间进展,每位会员都会有更多的观看数据需要被保存. 随着会员数量增长,更多的会员的观看…

来源:https://blog.csdn.net/bluishglc/article/details/79277455 引言在大数据的生态系统里,时间序列数据(Time Series Data,简称TSD)是很常见也是所占比例最大的一类数据,几乎出现在科学和工程的各个领域,一些常见的时间序列数据有:描述服务器运行状况的Metrics数据.各种IoT系统的终端数据.脑电图.汇率.股价.气象和天文数据等等,时序数据在数据特征和处理方式上有很大的共性,因此也催生了一些面向面向时序数据的特定工具,比如时…

以HADOOP为代表的云计算提供的仅仅是一个算法执行环境,为大数据的并行计算提供了在现有软硬件水平下最好的(近似)方法.并不能解决大数据应用中的全部问题.从详细应用而言,通过物联网方式接入IT圈的数据供应商(Data Provider)所面临的首要问题是数据分析的算法.其次才是算法的并行计算. 以汽车厂商(OEM,Tire1,Vendor,TSP)为例,所面临的大数据问题在 4V(Volume,Velocity,Variety,Veracity/Value)中,最突出的差异是Velocity,即…

Problem: ?? mining relationships in time series data; A new class of relationships in time series data. traditional methods: discover pair-wise relationships. Introduction: Challenge: discovery of complex patterns of relationships between individual…

It is important to note the distinction between time series and sequential data. In both cases, the data consist of a sequence, or list of values, in which the order is important. Time series is a subclass of sequential data where the longitudinal co…

From: Stanford University; Jure Leskovec, citation 6w+; Problem: subsequence clustering. Challenging: discover patterns is challenging because it requires simultaneous segmentation and clustering of the time series + interpreting the cluster results…

A sample network anomaly detection project Suppose we wanted to detect network anomalies with the understanding that an anomaly might point to hardware failure, application failure, or an intrusion. What our model will show us The RNN will train on a…

from here 论文Timeseries data mining(2012)中提出:时间序列数据挖掘包括7个基本任务和3个基础问题: 7 tasks: query by content clustering classification segmentation?? prediction anomaly detection motif discovery 3 Issues: data representation similarity measure indexing 现已有2013-201…