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- Research on Time Series Data Mining 时间序列数据挖掘研究
- A System of Time Series Data Mining Based on Hybrid Model 一种基于混合模型的时间序列数据挖掘系统
- Time series data mining using discrete wavelet transform 基于离散小波变换的时间序列数据挖掘
- Stock Market Time Series Data Mining Based on Regularized Neural Network and Rough Set 正则化训练的神经网络与粗集理论相结合的股票时间序列数据挖掘技术
- Time series data mining 时间序列数据挖掘
- Returns predicted future or historical values for time series data. 返回时序数据的将来或历史的预测值。
- 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。
- Based on the data mining of the time series,generally discretizes time series,then clusters different sub-pattern. 基于时间序列的数据挖掘时,一般需要对时间序列离散化,再聚类成不同的子模式。
- On the Select the Data Mining Technique page, under Which data mining technique do you want to use?, Select Microsoft Time Series, and then click Next. 在“选择数据挖掘技术”页的“您要使用何种数据挖掘技术?”下,选择“Microsoft时序”,再单击“下一步”。
- 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。
- The Decision Tree tab of the Microsoft Time Series Viewer in Data Mining Designer lets you view the decision tree that was created when the model was processed. 使用数据挖掘设计器中的Microsoft时序查看器的“决策树”选项卡,可以查看处理模型时创建的决策树。
- By using the Microsoft Time Series algorithm on historical data from the past three years, the company can produce a data mining model that forecasts future bike sales. 通过对过去三年的历史数据使用Microsoft时序算法,该公司可以建立一个数据挖掘模型,用于预测未来的自行车销售情况。
- Similarity search is just the research base of data mining on time series, since association, classify and clustering all need solve the similitude degree problem of time series. 相似性搜索是时间序列数据挖掘的研究基础,因为无论是分类、聚类还是关联规则挖掘,都需要解决时间序列的相似度问题,相似性搜索是时间序列数据挖掘的研究基础。
- The limitlessness,mobility,and irregularity of time series data stream make the traditional frequent-pattern mining algorithms difficult to extend to the mining problem of time series data stream. 时序数据流的无限性、流动性和不规则性使得传统的频繁模式挖掘算法难以适用。
- The limitlessness, mobility, and irregularity of time series data stream make the traditional frequent-pattern mining algorithms difficult to extend to the mining problem of time series data stream. 摘要时序数据流的无限性、流动性和不规则性使得传统的频繁模式挖掘算法难以适用。
- The outer frequency spectra of wind waves are estimated with the time series data of wave elevation measured in the laboratory wind wave flume. 利用实验室风浪槽内测得的波面序列资料估计风浪外频谱。
- Time series data is continuous and can be stored in a nested table or in a case table. 时序数据是连续的,可以存储在嵌套表或事例表中。
- Objective: Fit the forcast model that suit to the time series data of the Hospitalization Expenses of Injury Children. 摘要目的拟合适合儿童伤害住院费用时间序列资料的预测模型。
- On the basis of constructing the time series data with the same time interval by interpolation met... 计算实例表明,模型具有运算速度快、预测精度高的特点,是一种具有应用前景的软基预测新方法。
- The Microsoft Time Series algorithm is a regression algorithm for use in creating data mining models to predict continuous columns, such as product sales, in a forecasting scenario. Microsoft时序算法是一种回归算法,用于在预测方案中创建数据挖掘模型以预测连续列(如产品销量)。