A challenge in big data classification is the design of highly parallelized learning algorithms. One solution to this problem is applying parallel computation to different components of a learning model. In this paper, we first propose an extreme learning machine tree (ELM-Tree) model based on the heuristics of uncertainty reduction. In the ELM-Tree model, information entropy and ambiguity are ...

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...

A usual way of ASR accuracy evaluation is calculation of Word Error Rate (WER) and Sentence Error Rate (SER). The misrecognitions that contribute to WER are classified into three categories: deletions, insertions and substitutions. The paper presents a study about a contribution of intrinsic speech variabilities to the each of the error category. Decision tree (DT) analysis is used. Five DT sty...

Many state-of-the-art face recognition algorithms use image descriptors based on features known as Local Binary Patterns (LBPs). While many variations of LBP exist, so far none of them can automatically adapt to the training data. We introduce and analyze a novel generalization of LBP that learns the most discriminative LBP-like features for each facial region in a supervised manner. Since the ...

In the most common decision tree (DT) induction approaches, crossvalidation based processes validate the final DT model. This article answers many questions about advantages of using different types of committees constructed from the DTs generated within the validation process, over single validated DTs. Some new techniques of providing committee members and their collective decisions are intro...

Recommendation Systems (RSs) are used to provide users useful and effective suggestions. Effectiveness of RSs is depend on the quality of the suggestions. In this study, a new RS based on decision tree (DT) using implicit relevance feedback have been developed for movies. User behavior as implied relevance feedback is modeled by clickstreams. The DT constructed by Gini algorithm. The experiment...

Current techniques available for the characterization of membrane are destructive, including scanning electron microscopy, mercury intrusion porosimetry and size exclusion of particles. An alterative technique based on ultrasonic frequency domain reflectometry (UTDR) that allows easy, non-invasive and real-time analysis of membrane morphology would be of significant value to the membrane indust...

Android being a leading and the most popular operating system for smart phones and tablets, has also become a prime target for the attackers due to its growing users and it being an open source platform. This document describes the work done in detecting malware in the Android platform by performing static analysis on the permission based framework in Android platform. In our work, we have extr...

Accurate software effort estimation has been a challenge for many software practitioners and project managers. Underestimation leads to disruption in the project’s estimated cost and delivery. On the other hand, overestimation causes outbidding and financial losses in business. Many software estimation models exist; however, none has been proven to be the best in all situations. In this paper, ...

The paper presents a system using Decision tree, Particle swarm optimization, and Support vector regression to design a Median-type filter with a 2-level impulse detector for image enhancement, called DPSM filter. First, it employs a varying 2-level hybrid impulse noise detector (IND) to determine whether a pixel is contaminated by impulse noises or not. The 2-level IND is constructed by a deci...