Cancer Recognition From DNA Microarray Gene Expression Data Using Averaged One - Dependence Estimators

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود 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

Cancer Recognition from Dna Microarray Gene Expression Data Using Averaged One- Dependence Estimators

Cancer is a major leading cause of death and responsible for around 13% of all deaths world-wide. Cancer incidence rate is growing at an alarming rate in the world. Despite the fact that cancer is preventable and curable in early stages, the vast majority of patients are diagnosed with cancer very late. Therefore, it is of paramount importance to prevent and detect cancer early. Nonetheless, co...

متن کامل

Averaged One-Dependence Estimators: Preliminary Results

Naive Bayes is a simple, computationally efficient and remarkably accurate approach to classification learning. These properties have led to its wide deployment in many online applications. However, it is based on an assumption that all attributes are conditionally independent given the class. This assumption leads to decreased accuracy in some applications. AODE overcomes the attribute indepen...

متن کامل

Big Models for Big Data using Multi objective averaged one dependence estimators

Even though, many researchers tried to explore the various possibilities on multi objective feature selection, still it is yet to be explored with best of its capabilities in data mining applications rather than going for developing new ones. In this paper, multi-objective evolutionary algorithm ENORA is used to select the features in a multi-class classification problem. The fusion of AnDE (av...

متن کامل

Highly Scalable Attribute Selection for Averaged One-Dependence Estimators

Averaged One-Dependence Estimators (AODE) is a popular and effective approach to Bayesian learning. In this paper, a new attribute selection approach is proposed for AODE. It can search in a large model space, while it requires only a single extra pass through the training data, resulting in a computationally efficient two-pass learning algorithm. The experimental results indicate that the new ...

متن کامل

Ensemble Dependence Model Based Cancer Classification using Gene Microarray Data

DNA microarray technologies make it possible to simultaneously monitor thousands of genes expression levels. A topic of great interest is to study the different expression profiles between microarray samples from cancer patients and normal subjects, by classifying them at gene expression level. Currently, various clustering methods have been proposed in the literature to classify cancer and nor...

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: International Journal on Cybernetics & Informatics

سال: 2014

ISSN: 2320-8430,2277-548X

DOI: 10.5121/ijci.2014.3201