Structured Machine Learning for Soft Classification with Smoothing Spline ANOVA and Stacked Tuning, Testing, and Evaluation

Component Selection and Smoothing in Multivariate Nonparametric Regression

We propose a new method for model selection and model fitting in multivariate nonparametric regression models, in the framework of smoothing spline ANOVA. The “COSSO” is a method of regularization with the penalty functional being the sum of component norms, instead of the squared norm employed in the traditional smoothing spline method. The COSSO provides a unified framework for several recent...

Statistical Learning in Medical Data Analysis

This article provides a tour of statistical learning regularization methods that have found application in a variety of medical data analysis problems. The uniting feature of these methods is that they involve an optimization problem which balances fidelity to the data with complexity of the model. The two settings for the optimization problems considered here are Reproducing Kernel Hilbert Spa...

An Introduction to (Smoothing Spline) ANOVA Models in RKHS, With Examples in Geographical Data, Medicine, Atmospheric Science and Machine Learning.

Variable Selection for Support Vector Machines via Smoothing Spline Anova

It is well-known that the support vector machine paradigm is equivalent to solving a regularization problem in a reproducing kernel Hilbert space. The squared norm penalty in the standard support vector machine controls the smoothness of the classification function. We propose, under the framework of smoothing spline ANOVA models, a new type of regularization to conduct simultaneous classificat...

Fault Detection of Anti-friction Bearing using Ensemble Machine Learning Methods

Anti-Friction Bearing (AFB) is a very important machine component and its unscheduled failure leads to cause of malfunction in wide range of rotating machinery which results in unexpected downtime and economic loss. In this paper, ensemble machine learning techniques are demonstrated for the detection of different AFB faults. Initially, statistical features were extracted from temporal vibratio...