Secure training of decision trees with continuous attributes

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Fuzzy Handling of Continuous-Valued Attributes in Decision Trees

Classical crisp decision trees (DT) are widely applied to classiication tasks. Nevertheless, there are still a lot of problems especially when dealing with numerical (continuous-valued) attributes. Some of those problems can be solved using fuzzy decision trees (FDT). This paper proposes a method for handling continuous-valued attributes with automatically generated (as opposed to user deened) ...

متن کامل

Learning decision trees with taxonomy of propositionalized attributes

We introduce Propositionalized Attribute Taxonomy guided Decision Tree Learner (PAT-DTL), an inductive learning algorithm that exploits a taxonomy of propositionalized attributes as prior knowledge to generate compact decision trees. Since taxonomies are unavailable in most domains, we also introduce Propositionalized Attribute Taxonomy Learner (PAT-Learner) that automatically constructs taxono...

متن کامل

Decision Trees and Multi-Valued Attributes

Common induction systems that construct decision-trees have been reported to operate unsatisfactorily when there are attributes with varying numbers of discrete possible values. This paper highlights the deficiency in the evaluation of the relevance of attributes and examines a proposed solution. An alternative method of selecting an attribute is introduced which permits the use of redundant at...

متن کامل

Building multi-way decision trees with numerical attributes

Decision trees are probably the most popular and commonly used classification model. They are recursively built following a top-down approach (from general concepts to particular examples) by repeated splits of the training dataset. When this dataset contains numerical attributes, binary splits are usually performed by choosing the threshold value which minimizes the impurity measure used as sp...

متن کامل

Improvement of Decision Accuracy Using Discretization of Continuous Attributes

The naïve Bayes classifier has been widely applied to decisionmaking or classification. Because the naïve Bayes classifier prefers to dealing with discrete values, an novel discretization approach is proposed to improve naïve Bayes classifier and enhance decision accuracy in this paper. Based on the statistical information of the naïve Bayes classifier, a distributional index is defined in the ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Proceedings on Privacy Enhancing Technologies

سال: 2020

ISSN: 2299-0984

DOI: 10.2478/popets-2021-0010