Background: Microarray experiments can simultaneously determine the expression of thousands of genes. Identification of potential genes from microarray data for diagnosis of cancer is important. This study aimed to identify genes for the diagnosis of acute myeloid and lymphoblastic leukemia using a sparse feature selection method. Materials and Methods: In this descriptive study, the expressio...

The recognition of handwritten numeral is an important area of research for its applications in post office, banks and other organizations. This paper presents automatic recognition of handwritten Kannada numerals using both unsupervised and supervised classifiers. Four different types of structural features, namely, direction frequency code, water reservoir, end points and average boundary len...

A problem with automatic classifiers is that there is no way to know if a particular classification is just a guess or a certain answer. Reliable classification is the task of predicting whether a certain instance is correctly classified or not, i.e., a classification is classified as either reliable or unreliable. When the classification is classified as unreliable, it is like saying “I do not...

Millions of people are affected by the disease Knee Osteoarthritis, and prevalence condition is steadily increasing. osteoarthritis has a significant impact on people's lives generating increased worry, mental health disorders, physical problems. Early detection knee critical for decreasing consequences, numerous studies being conducted to classify osteoarthritis. In this study, deep CNN classi...

Human learners have the natural ability to use knowledge gained in one setting for learning a different but related setting. This transfer from task another is essential effective learning. In this paper, we study context of nonparametric classification based on observations distributions under posterior drift model, which general framework and arises many practical problems. We first establish...

Different approaches have been proposed for feature selection to obtain suitable features subset among all features. These methods search feature space for feature subsets which satisfies some criteria or optimizes several objective functions. The objective functions are divided into two main groups: filter and wrapper methods.  In filter methods, features subsets are selected due to some measu...

The aim of this study is to introduce a new methodology for isolation of ectopic rhythms of ambulatory electrocardiogram (ECG) holter data via appropriate statistical analyses imposing reasonable computational burden. First, the events of the ECG signal are detected and delineated using a robust wavelet-based algorithm. Then, using Binary Neyman-Pearson Radius test, an appropriate classifie...