Information Theory and Decision Tree

نویسنده

  • Jianxin Wu
چکیده

3 Basics of information theory 3 3.1 Entropy and uncertainty . . . . . . . . . . . . . . . . . . . . . . . 4 3.2 Joint and conditional entropy . . . . . . . . . . . . . . . . . . . . 4 3.3 Mutual information and relative entropy . . . . . . . . . . . . . . 5 3.4 Some inequalities . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.5 Entropy of discrete distributions . . . . . . . . . . . . . . . . . . 7

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Provide a Predictive Model to Identify People with Diabetes Using the Decision Tree

Background: Today, in most hospitals in Iran, there is an extensive database of patient characteristics that includes a large amount of information related to medical, family and medical records. Finding a knowledge model of this information can help to predict the performance of the medical system and improve educational processes. Methods: Data mining techniques are analytical tools that are...

متن کامل

Evaluation of liquefaction potential based on CPT results using C4.5 decision tree

The prediction of liquefaction potential of soil due to an earthquake is an essential task in Civil Engineering. The decision tree is a tree structure consisting of internal and terminal nodes which process the data to ultimately yield a classification. C4.5 is a known algorithm widely used to design decision trees. In this algorithm, a pruning process is carried out to solve the problem of the...

متن کامل

Comparison of gestational diabetes prediction with artificial neural network and decision tree models

Background: Gestational diabetes mellitus (GDM) is one of the most common metabolic disorders in pregnancy, which is associated with serious complications. In the event of early diagnosis of this disease, some of the maternal and fetal complications can be prevented. The aim of this study was to early predict gestational diabetes mellitus by two statistical models including artificial neural ne...

متن کامل

Comparing different stopping criteria for fuzzy decision tree induction through IDFID3

Fuzzy Decision Tree (FDT) classifiers combine decision trees with approximate reasoning offered by fuzzy representation to deal with language and measurement uncertainties. When a FDT induction algorithm utilizes stopping criteria for early stopping of the tree's growth, threshold values of stopping criteria will control the number of nodes. Finding a proper threshold value for a stopping crite...

متن کامل

MMDT: Multi-Objective Memetic Rule Learning from Decision Tree

In this article, a Multi-Objective Memetic Algorithm (MA) for rule learning is proposed. Prediction accuracy and interpretation are two measures that conflict with each other. In this approach, we consider accuracy and interpretation of rules sets. Additionally, individual classifiers face other problems such as huge sizes, high dimensionality and imbalance classes’ distribution data sets. This...

متن کامل

Anomaly Detection Using SVM as Classifier and Decision Tree for Optimizing Feature Vectors

Abstract- With the advancement and development of computer network technologies, the way for intruders has become smoother; therefore, to detect threats and attacks, the importance of intrusion detection systems (IDS) as one of the key elements of security is increasing. One of the challenges of intrusion detection systems is managing of the large amount of network traffic features. Removing un...

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

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017