Quantifying Performance Appraisal Parameters: A Forward Feature Selection Approach

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

Performance of Feed Forward Neural Network for a Novel Feature Selection Approach

Feature selection for classification of cancer data is to discover gene expression profiles of diseased and healthy tissues and use the knowledge to predict the health state of new sample. It is usually impractical to go through all the details of the features before picking up the right features. The differentially expressed genes or biomarker gene selection is the preprocessing task for cance...

متن کامل

Interleaving Forward Backward Feature Selection

Selecting appropriate features has become a key task when dealing with high-dimensional data. We present a new algorithm designed to find an optimal solution for classification tasks. Our approach combines forward selection, backward elimination and exhaustive search. We demonstrate its capabilities and limits using artificial and real world data sets. Regarding artificial data sets interleavin...

متن کامل

Forward Semi-supervised Feature Selection

Traditionally, feature selection methods work directly on labeled examples. However, the availability of labeled examples cannot be taken for granted for many real world applications, such as medical diagnosis, forensic science, fraud detection, etc, where labeled examples are hard to find. This practical problem calls the need for “semi-supervised feature selection” to choose the optimal set o...

متن کامل

A Classification Method for E-mail Spam Using a Hybrid Approach for Feature Selection Optimization

Spam is an unwanted email that is harmful to communications around the world. Spam leads to a growing problem in a personal email, so it would be essential to detect it. Machine learning is very useful to solve this problem as it shows good results in order to learn all the requisite patterns for classification due to its adaptive existence. Nonetheless, in spam detection, there are a large num...

متن کامل

Forward feature selection using Residual Mutual Information

In this paper, we propose a hybrid filter/wrapper approach for fast feature selection using the Residual Mutual Information (RMI) between the function approximator output and the remaining features as selection criterion. This approach can handle redundancies in the data as well as the bias of the employed learning machine while keeping the number of required training and evaluation procedures ...

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: Indian Journal of Science and Technology

سال: 2016

ISSN: 0974-5645,0974-6846

DOI: 10.17485/ijst/2016/v9i21/95122