The traditional data-driven prognostic approach is to construct multiple candidate algorithms using a training data set, evaluate their respective performance using a testing data set, and select the one with the best performance while discarding all the others. This approach has three shortcomings: (i) the selected standalone algorithm may not be robust, i.e., it may be less accurate when the ...

In this paper, we review the k–Fold Cross Validation (KCV) technique, applied to the Support Vector Machine (SVM) classification algorithm. We compare several variations on the KCV technique: some of them are often used by practitioners, but without any theoretical justification, while others are less used but more rigorous in finding a correct classifier. The last ones allow to establish an up...

The vocal fold mucosa is a biomechanically unique tissue comprised of a densely cellular epithelium, superficial to an extracellular matrix (ECM)-rich lamina propria. Such ECM-rich tissues are challenging to analyze using proteomic assays, primarily due to extensive crosslinking and glycosylation of the majority of high M(r) ECM proteins. In this study, we implemented an LC-MS/MS-based strategy...

The aim of this study is to show the artificial neural network (ANN) on classification of mineral based on color values of pixels. Twenty two images were taken from the thin sections using a digital camera mounted on the microscope and transmitted to a computer. Images, under both plane-polarized and cross-polarized light, contain maximum intensity. To select training and test data, 5-fold-cros...

Often, in a regression situation with many variables, a sequence of submodels is generated containing fewer variables using such methods as stepwise addition as deletion of variables, or "best subsets". The question is which of this sequence of submodels is "best", and how can submodel perfornance be evaluated. This was explored in Breiman [1988] for a fixed X-design. This is a sequel exploring...

Seizure type identification is essential for the treatment and management of epileptic patients. However, it a difficult process known to be time consuming labor intensive. Automated diagnosis systems, with advancement machine learning algorithms, have potential accelerate classification process, alert patients, support physicians in making quick accurate decisions. In this paper, we present no...

Recommender systems have been widely used in e-commerce applications. They are a subclass of information filtering system, used to either predict whether a user will prefer an item (prediction problem) or identify a set of k items that will be user-interest (Top-k recommendation problem). Demanding sufficient ratings to make robust predictions and suggesting qualified recommendations are two si...

-A scene independent linear transformation called – multitemporal Kauth-Thomas transformation (MKT) was implemented in this land surface change monitoring due to mining activities. 5-fold cross validation results indicated the high feasibility of using the MKT method with a computer-based hybrid unsupervised and supervised classification approach for mining monitoring.