Time series data set comes with a temporal ordering.
时间序列数据集伴随着一个时间上的排序。
Time series data set comes with a temporal ordering.
时间序列数据是以时间为指标的一个随机变量序列。
Mining time series data with association rules is a new field.
采用关联规则挖掘时序数据是较新的研究领域。
How to detect if change in time series data is no longer significant?
如何检测是否在时间序列数据的变化不再明显？
How to customize axis when plot multiple time series data in 1 panel?
如何自定义轴当绘制多个时间序列数据在1小组？
A time series data set is a sequence of random variables indexed by time.
时间序列数据是以时间为指标的一个随机变量序列。
In the field of customer, there exist a large number of time series data.
在客户领域，存在着大量的时间序列数据。
How to remove subjects who have missing measurements in time series data?
如何去除那些失踪的测量在时间序列数据吗？
How to handle time series data with other attributes in machine learning?
如何在机器学习的其他属性的处理时间序列数据？
Research on time series data mining is one of important hot spots of data mining.
目前时间序列的数据挖掘是数据挖掘的重要研究热点之一。
First, the testing data must be interpolated and the basic time series must be built.
对经过预处理的测试数据进行三次样条插值，得到基本时间序列。
High dimensionality is the main difficulty of similarity search over time-series data.
数据的高维度是造成时序数据相似性搜索困难的主要原因。
And ultra high frequency time series is tick-by-tick data, which contain plenty of market information.
而超高频时间序列是市场上每笔交易的实时数据，其中包含了丰富的市场信息。
And ultra high frequency time series is tick-by-tick data, which contain plenty of market information.
而超高频时间序列是市场上每笔交易的实时数据，其中包含了丰富的市场信息。
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