现代计算机(普及版)
現代計算機(普及版)
현대계산궤(보급판)
MODERN COMPUTER
2015年
3期
26-30
,共5页
时间序列%增量式学习%决策树%算法研究
時間序列%增量式學習%決策樹%算法研究
시간서렬%증량식학습%결책수%산법연구
Time Series%Incremental Learning%Decision Tree%Algorithm Research
数据挖掘技术已经应用到很多研究领域中,数据挖掘的类型也越来越复杂。其中一类数据本身是有顺序相关的,且是实值型数据,定义具有这样特征的数据为时间序列数据,使用常见的数据挖掘方法从时间序列数据中进行知识学习是不适用的。并且随着大数据理论的不断发展,能够增量式地处理数据以减小对时间和存储空间的需求。基于时间序列数据维度高、实值有序、数据间存在自相关性等特点,提出一种增量式决策树的时间序列分类算法。
數據挖掘技術已經應用到很多研究領域中,數據挖掘的類型也越來越複雜。其中一類數據本身是有順序相關的,且是實值型數據,定義具有這樣特徵的數據為時間序列數據,使用常見的數據挖掘方法從時間序列數據中進行知識學習是不適用的。併且隨著大數據理論的不斷髮展,能夠增量式地處理數據以減小對時間和存儲空間的需求。基于時間序列數據維度高、實值有序、數據間存在自相關性等特點,提齣一種增量式決策樹的時間序列分類算法。
수거알굴기술이경응용도흔다연구영역중,수거알굴적류형야월래월복잡。기중일류수거본신시유순서상관적,차시실치형수거,정의구유저양특정적수거위시간서렬수거,사용상견적수거알굴방법종시간서렬수거중진행지식학습시불괄용적。병차수착대수거이론적불단발전,능구증량식지처리수거이감소대시간화존저공간적수구。기우시간서렬수거유도고、실치유서、수거간존재자상관성등특점,제출일충증량식결책수적시간서렬분류산법。
Data mining technology has been attracting great interest in a vast array of research areas, and their types are more and more complex. The data is related and ordered set of real valued variables, and then such data with above characters is called time series. The following conclusion is that common method of data mining method can't be suit to time series data mining. And with the continuous development of the theory of big data, incremental method is essential in order to decrease temporal and space demand for implement of time series. Focuses on the research on time series classification according to time series features of high dimensionality, ordered real-valued vari-ables, auto-correlation and so on. And proposes incremental decision-tree algorithm for time series classification.