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Decision tree classifier construction method based on uncertain continuous attributes

A decision tree classification and construction method technology, applied in the field of decision tree classifier construction based on uncertain continuous attributes, can solve problems such as classification and prediction of uncertain continuous attributes, and achieve high classification accuracy

Inactive Publication Date: 2017-05-03
SICHUAN YONGLIAN INFORMATION TECH CO LTD
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Problems solved by technology

[0003] Aiming at solving the problem of classification and prediction of uncertain continuous attributes and improving the accuracy of its classification and prediction, the present invention proposes a decision tree classifier construction method based on uncertain continuous attributes

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  • Decision tree classifier construction method based on uncertain continuous attributes
  • Decision tree classifier construction method based on uncertain continuous attributes
  • Decision tree classifier construction method based on uncertain continuous attributes

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Embodiment Construction

[0025] In order to solve the problem of classification and prediction of uncertain continuous attributes and improve the accuracy of its classification and prediction, combined with figure 1 The present invention has been described in detail, and its specific implementation steps are as follows:

[0026] Step 1: Suppose there are X samples in the training set of uncertain continuous attributes, and the number of attributes is n, that is, n=(S 1 , S 2 ,…S n ), while splitting the attribute S i Corresponds to m classes L, where L r ∈(L 1 , L 2 ...,L m ), i ∈ (1, 2..., n), r ∈ (1, 2..., m). S i ∈(S 1 , S 2 ,…S n ), where the attribute value is uncertain.

[0027] Step 2: Put the uncertain continuous data attribute S i attribute value S ij Merge sort, according to class pair uncertain continuous data attribute S i Attribute value S ij operation, denoted as the probability sum P(S ij ), the probability potential P(S ij , L r ). Its specific operation process is ...

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Abstract

The invention discloses a decision tree classifier construction method based on uncertain continuous attributes. The method comprises the following steps: classifying X sample data in which uncertain continuous data exists; ordering by merging attribute values Sij of uncertain continuous data attributes Si, performing attribute value Sij operation on the uncertain data attributes Si according to classes, and denoting as the probabilistic summation P(Sij); processing the classes to obtain the probabilistic cardinality P(Sij, Lr) of each branched attribute value, creating a decision tree, and selecting splitSi according to a target function created by the invention, and stopping creating the tree according to a condition. The constructed decision tree can better avoid the problem that the information bias is large in order of magnitude, and can realize the classification and prediction function of an object, namely, the uncertain continuous attributes; the constructed decision tree is high in classification accuracy; and the constructed decision tree is more suitable for an application for an actual data mining problem.

Description

technical field [0001] The invention relates to the fields of machine learning, artificial intelligence and data mining, in particular to a method for constructing a decision tree classifier based on uncertain continuous attributes. Background technique [0002] Decision tree research is an important and active research topic in data mining and machine learning. The proposed algorithm is widely used in practical problems, such as ID 3 , CART and C4.5, this kind of algorithm is mainly to study the problem of accuracy. With the advancement of science and technology, in recent years, uncertain data frequently appear in practical applications, including wireless sensor networks, radio frequency identification, privacy protection and other fields. The characteristic of its data is that the data value is not definite, that is, it represents a data point, and its representation method is to take multiple values ​​as a whole, and use a certain probability distribution as the corre...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/24
Inventor 金平艳胡成华
Owner SICHUAN YONGLIAN INFORMATION TECH CO LTD
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