Human Sit Down Position Detection Using Data Classification and Dimensionality Reduction

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

Dimensionality Reduction and Improving the Performance of Automatic Modulation Classification using Genetic Programming (RESEARCH NOTE)

This paper shows how we can make advantage of using genetic programming in selection of suitable features for automatic modulation recognition. Automatic modulation recognition is one of the essential components of modern receivers. In this regard, selection of suitable features may significantly affect the performance of the process. Simulations were conducted with 5db and 10db SNRs. Test and ...

متن کامل

Diagnosis of Diabetes Using an Intelligent Approach Based on Bi-Level Dimensionality Reduction and Classification Algorithms

Objective: Diabetes is one of the most common metabolic diseases. Earlier diagnosis of diabetes and treatment of hyperglycemia and related metabolic abnormalities is of vital importance. Diagnosis of diabetes via proper interpretation of the diabetes data is an important classification problem. Classification systems help the clinicians to predict the risk factors that cause the diabetes or pre...

متن کامل

Classification Constrained Dimensionality Reduction

Dimensionality reduction is a topic of recent interest. In this paper, we present the classification constrained dimensionality reduction (CCDR) algorithm to account for label information. The algorithm can account for multiple classes as well as the semi-supervised setting. We present an out-of-sample expressions for both labeled and unlabeled data. For unlabeled data, we introduce a method of...

متن کامل

Dimensionality Reduction using Noisy Distance Data

The basic idea behind most dimensionality reduction algorithms is to find a low dimensional embedding of high dimensional data while roughly preserving the local relationships between the data points. The inputs to these algorithms are usually the point coordinates in the higher dimensional space or some form of mutual distance data between the points in the higher dimensional space. However, v...

متن کامل

Hyperspectral Data Dimensionality Reduction Using Hybrid Approach

Hyperspectral data contain a large volume of information. This abundance of data is hard to exploit due to high computational cost involved in processing this data. Dimensionality reduction deals with transforming high dimensional data in to lower dimensional space without losing significance of the High dimensional data. In this paper, a new methodology has been proposed that is based on exist...

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: Advances in Science, Technology and Engineering Systems Journal

سال: 2017

ISSN: 2415-6698

DOI: 10.25046/aj020395