Abstract. Independent from the concrete definition of the term "data quality" consistency always plays a major role. There are two main points when dealing with the data quality of a database: Firstly, the data quality has to be measured, and secondly, if is necessary, it must be improved. A classifier can be used for both purposes ...

The exponential rise in the amount of data has fueled various facets in data science and data engineering. Classification is a supervised machine learning task that underlies several diagnosis systems and rule-based decision support systems. The efficiency of a rule-based classifier depends on factors such as quality of the rules in …

In Section 2, we discuss the background concerned with the improvement of soldering quality and data mining approaches used in the electronics packaging. The clustering and decision tree algorithms are reviewed in Section 3. Section 4 describes the research methodology for developing the proposed classifier and the empirical …

Distilling actionable patterns from large-scale streaming data in the presence of concept drift is a challenging problem, especially when data is polluted with noisy labels. To date, various data stream mining algorithms have been proposed and extensively used in many real-world applications. Considering the functional complementation of classical …

The data imbalance problem coming from the safe condition of the monitoring target is solved by augmenting the training data with those acquired from another mine and employing class weighting. After training, an optimal classifier is chosen considering the loss function, accuracy and F β score. The optimal classifier shows very high accuracy ...

First Online: 21 May 2020. 3431 Accesses. Part of the book series: Undergraduate Topics …

Mining non stationary and imbalanced data streams is a relatively new area of research. In this paper, we propose the Gene Expression Programming (GEP) classifier with drift detection and data ...

However, in proper mining terms, the size of the holes is expressed in mesh sizes. In simple terms, mesh size is the number of openings per linear inch. If the mesh is 2, it means that every square inch contains 2 * 2 holes, which is 4. Here is a table showing three classifier sizes expressed in inches, mesh size, and openings per square inch.

1. Introduction. Water composes more than two-thirds of the earth's surface and is a critical resource for living organisms. However, despite its abundance, the consumable form of water is limited [1].Moreover, numerous ailments transmit through water; hence, real-time monitoring of water quality (WQ) is essential [2]monly, …

DOI: 10.1016/j.eswa.2011.11.097 Corpus ID: 11370457; Development of a soldering quality classifier system using a hybrid data mining approach @article{Tsai2012DevelopmentOA, title={Development of a soldering quality classifier system using a hybrid data mining approach}, author={Tsung-Nan Tsai}, journal={Expert …

Data mining classifier; Water quality index (WQI) Classification; Download conference paper PDF 1 Introduction. Water quality has become a concern to the world, and since last decades' there were many research focused on water quality (WQ) . Our water sources vary from surface water like river, lake, and coastal areas and …

Techniques To Evaluate Accuracy of Classifier in Data Mining - GeeksforGeeks. Last Updated : 30 Jan, 2023. Pre-requisites: Data Mining. Data Mining can be referred to as knowledge mining from data, …

Due to the noisy and high-dimensional character of the data combined with a small sample size, semi-supervised classification of high-dimensional data with few labeled samples is a significant problem in machine learning and data mining. To address these challenges, we first propose a novel feature evaluation function that combines the advantages of the …

To compare the performance of various classifiers, we have already transformed the output variable to a binary as "good quality" if (qualityge 7) and 'bad quality' if if (quality<7).

This paper presents the comparison of accuracies for the five classifiers (NB, MLP, J48, SMO, and IBk) based on a 10-fold cross validation as a test method with respect to water quality from the ...

High weir type high quality spiral classifier is mainly used for ore classification with overflow particle size of 0.83-0.15mm. 2. Submergence type: all spiral blades at overflow end are immersed below overflow surface. Submergence type high quality spiral classifier is mainly suitable for ore classification with overflow particle size of 0.15 ...

Mining non stationary and imbalanced data streams is a relatively new area of research. In this paper, we propose the Gene Expression Programming (GEP) classifier with drift detection and data reuse for mining imbalanced data streams. GEP is used to evolve a complex expression tree returning predictions.

The extracted features have been fed to data mining based Decision tree (DT) classifier in order to discriminate the PQ distur bances. These aforementioned methods are also implemented on real signals. S-transform is implemented for analysis of different type of power quality (PQ) disturbance signals for discriminate the PQ distur bances ...

DOVE Spiral Classifier, also referred to as Screw Classifier, or Spiral Mineral Separator, is highly efficient classifier designed for closed circuit wet classification and separation of the Slimes (Fines) from a sandy sized (Coarse) material. It is well suited for classification, where a two product size-split is required. Due to inherent operational qualities, DOVE Spiral …

JinPeng Mining has very strict production management and advanced production technology, and has achieved ISO 9001: 2008. We own various kinds of devices such as: CNC automatic cutting machine, CNC automatic welding machine, 5 meters vertical CNC lathe, CNC lathe, CNC boring machine, and the largest lathe in Shandong provence with …

Shadbahr et al. highlight the importance of evaluating imputation quality when building classification models for incomplete data. They demonstrate how a model built on poorly imputed data can ...

Er, and atasoy [1,2,3] proposed an approach based on support vector machine classifier to classify the quality of a wine It uses three classification techniques. Chen et al. [4, 5, 6] Based on ...

A classifier can be used for both purposes regarding consistency …

There are two main points when dealing with the data quality of a database: Firstly, the data quality has to be measured, and secondly, if is necessary, it must be improved. A classifier can be ...

In this project I wanted to compare several classification algorithms to predict wine quality which has a score between 0 and 10. ... validation scores and recall results of all models we can see that the best …

The objective of this paper is twofold. First; we demonstrate the application of data mining techniques to predict quality indicators (TDS, Hardness, Na, Cl, SO $$_{4}$$ 4 ) of groundwater data measured in three different basins of Şanlıurfa. The determination of the potable water classes was predicted using six well-known classifiers with respect to …

In this study, quality grading of raisins using image processing and data mining based classifiers was investigated. Images from four different classes of raisins (green, green with tail, black, and black with tail) were acquired using a color CCD camera.

Rake Classifier. The Rake Classifier is designed for either open or closed circuit operation. It is made in two types, type "C" for light duty and type "D" for heavy duty. The mechanism and tank of both units are of sturdiest construction to meet the need for 24 hour a day service. Both type "C" and type "D" Rake Classifiers ...

Thereby achieving a reasonable classifier performance is an increasingly important goal. This paper aims to empirically show how classifier performance can be improved by knowledge-driven data preparation using business, data and methodological know-how. To point out the variety of knowledge-driven approaches, we firstly introduce an advanced ...

Abstract. In this study, quality grading of raisins using image processing and data mining based classifiers was investigated. Images from four different classes of raisins (green, green with tail, black, and black with tail) were acquired using a color CCD camera. After pre-processing and segmentation of images, 44 features including 36 color ...