We consider the smoothed version of sliced average variance estimation (SAVE) dimension reduction method for dealing with spatially dependent data that are observations a strongly mixing random field. propose kernel estimators interest matrix and effective (EDR) space, show their consistency.

Breast cancer is the most frequently occurring disease in women. It reported almost 14% of cancers Indian women are breast cancer. becomes very crucial to predict earlier minimize deaths. This research article helps and reduce immature deaths India. In this paper, authors have used Logistic Regression method classify disease. The simulate results using logistic regression with 10-fold cross-val...

Support vector regression (SVR) is a powerful kernel-based method which has been successfully applied in problems. Regarding the feature-weighted SVR algorithms, its contribution to model output taken into account. However, performance of subject feature weights and time consumption on training. In paper, an efficient proposed. Firstly, value constraint each weight obtained according maximal in...

The development of sparse techniques presents a major challenge to complex nonlinear high-dimensional data. In this paper, we propose novel feature selection method for support vector regression, called FS-NSVR, which first attempts solve the problem in regression technology field. FS-NSVR preserves representative features selected system due its use matrix original space. is challenging mixed-...