Best Mining Software Of 2019
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When choosing an algorithm, using the algorithm which is known as giving good results without comparing its performance to different algorithms or comparing different algorithms by adhering to a single statistical criterion may give misleading results. Using an algorithm that is considered to only give good results without considering its suitability in data may lead to inaccurate results. Likewise, when determining the best algorithm, comparing under a single criterion may cause a wrong selection. Therefore, in this study, Naive Bayes, Bayes network, J48, logistic regression, multilayer perceptron, random forest and classification algorithms were determined with pre-elimination and then, determined algorithms were compared again with accuracy, F-measure, Roc area, recall, precision, and RMSE criterions. As a result of the analysis, the logistic regression classification algorithm was determined as the best algorithm. In conclusion, the logistic regression algorithm was used in the analysis of default risk.
The WEKA data-mining implementation software was developed by the University of New Zealand. It is an open source software program written in Java under General Public License. It contains several supervised and unsupervised methods such as classification, clustering, association, and data visualization. For this study, the WEKA 3.9 implementation and its experimenter user interface were used for the classification of the algorithms as well as to specify risk attributes using the logistic regression algorithm.
Our study used an analysis to discover the most suitable classification algorithm to identify credit risks and estimate the likelihood of default. This analysis was carried out using WEKA software and by applying 12 variables such as demographic characteristics of heads of household, total income, debt payment status, and regional information. Six classification algorithms were used (Bayes network, Naive Bayes, J48, random forest, multilayer perceptron, and logistic regression). The performances of the algorithms were compared according to accuracy, root mean squared error, ROC area, F-measure, precision, and recall criteria, and the logistic regression classification algorithm was found to be the best algorithm.
This study contributes to existing literature by suggesting classification algorithms that can be used to determine credit risks. Additionally, we identified the variables that can be used in determining the default risk, which will assist future researchers in this field. The study is also valuable in terms of illustrating that DM can be used in the determination of credit risk within the framework of the development of academic studies both in Turkey and globally. Because there are a limited number of studies on the subject of default risk being analyzed using DM applications and WEKA software, this study will contribute to filling the gap in the field.
Some research communities are also building online platforms for sharing research software services. The SoBigData Lab , for instance, provides a cloud service for data analytics, with a focus on social mining research. OceanTEA provides an online service for analyzing ocean observation data . The integrated toolchain LabPal for running, processing, and including the results of computer experiments in scientific publications is presented in . The tool Qresp for curating, discovering and exploring reproducible scientific papers is presented in . Generic services such as BinderHub  and Code Ocean  support online execution of reproducible code.
In the context of open science and research software, research software observatories can be considered in three different ways. First, in terms of describing a research software observatory for FAIR and open research software, that will allow scientists to share software and observations on the status of this software. A research software observatory could support open science research and encourage best practice among research communities. Second, one could consider the research software used for processing scientific data and producing observations (analytics) in ways that respect the FAIR and open principles. Third, the opportunities and challenges of cataloging research software with appropriate citation links in observatories can be explored. Research software observatories need to support metadata for research software classification and citation to further empower researchers to find, access and reuse relevant and interoperable research software.
As the New Year begins, Micromine is reminding mining companies to update their software to avoid potential cyber-security breaches, data loss, system integration issues and operational downtime in 2019.
Micromine Chief Technology Officer, Ivan Zelina, said: Software updates are often overlooked as they are not as visible as other business processes, but the value of new software versions should not be underestimated in our current, highly digitalised mining environment.
The software includes overclocking, monitoring, fan speed control and remote interface capabilities, among others. With ASIC, FGPA & GPU and multi pool support, CGminer is more than an adequate solution to handle your mining operation.
The software allows you to choose which coins you wish to mine per the connected mining device (GPU, ASIC, FGPA). MultiMiner is also packed with additional features such as an option to choose your mining strategy, remote access to your rig and tooltips to get you familiar with the complicated mining terms.
July also saw a major decrease in the use of Cryptoloot, as it fell to tenth in the top malware list, from third in June 2019. Cryptoloot has dominated the top malware list for the past year and a half, and was ranked the second most common malware variant seen in the first half of 2019, impacting 7.2% of organizations worldwide. We believe the decline is linked to its main competitor, Coinhive, closing its operations earlier in 2019. Threat actors are simply turning to alternative crypto-mining malware such as XMRig and Jsecoin.
This article focuses in selecting the best free software for performing data mining. Hopefully, there will be something of interest here for anyone who needs to make strategic decisions when confronted with large amounts of information.
Take for instance the 2 new booming languages in the TIOBE index top 20: Scratch and Rust. Scratch is meant to learn programming and is very popular in elementary and secondary schools, whereas Rust is a safe and high performance programming language for experts. In other words, they serve different purposes. The same holds for the top 4 languages. Python is great for data mining, AI programming, statistical programs, research projects, web sites, small glue programs and learning how to program. The second language, C, is the best language for writing small, embedded, safety-critical and high performance programs. C++ on the other hand, is the top favorite language in case you need all the requirements of C but you are going to write a large software system. Finally, Java is best in back ends of business applications and writing apps for Android. So if you want to use a programming language, do your research and select it with care! --Paul Jansen CEO TIOBE Software
Methods: In this study, we assessed the ability of five popular classifiers (J48, AdaboostM1, SMO, Bayes Net, and Naïve Bayes) to identify individuals with diabetes based on nine non-invasive and easily obtained clinical features, including age, gender, body mass index (BMI), hypertension, history of cardiovascular disease or stroke, family history of diabetes, physical activity, work stress, and salty food preference. A total of 4205 data entries were obtained from annual physical examination reports for adults in the Shengjing Hospital of China Medical University during January-April 2017. Weka data mining software was used to identify the best algorithm for diabetes classification.
Mining warrants a longer explanation. But put simply, it is a way to take part in the network by helping to validate transactions and secure the network. You generally download a piece of mining software for a specific coin, and off you go. In return for your work, you are rewarded with coins!
Then they started to use graphic processors and FPGA (field-programmable gate array), but soon they also ceased to be quite useful. ASIC miner is the best bitcoin miner of the latest generation. It provides a higher cryptocurrency mining speed, the machine heats less and consumes less electricity.
The international company has branches in the USA and China. The brand specializes in diverse digital technology. The brand is currently releasing one of the best ASIC Bitcoin mining hardware called Terminator T3.
The abbreviated name sounds like Ebang. The main field of activity of the company is the creation and sale of optical fiber for telecommunications. The latest ASICs mining equipment is one of the best using ASICs and competes with Bitmain.
\"She then used those misconfigured accounts to hack in and download the data of more than 30 entities, including Capital One bank,\" the DOJ stated in the press release. \"With some of her illegal access, she planted cryptocurrency mining software on new servers with the income from the mining going to her online wallet.\" 153554b96e