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CI5X Series Impact Crushers

CI5X series impact crusher is a new generation of coarse and medium crushed products designed to meet customers needs for high profit, low cost, energy saving and consumption reduction. It is the guarantee for large-volume production line c

Mining, metallurgy, construction, chemical, cement, refractory material, etc.

Parameter


Model Specifications (mm) Feed opening (mm) Max. feed size (mm) Capacity (t/h) Power (kW) Weight (t) Dimensions (mm)
CI5X1315 Φ1300×1500 1540×930 600 250-350 250 20 2880×2755×2560
CI5X1520 Φ1500×2000 2040×520 (2040×995) 350(700) 400-600 2×250 (2×200) 30 3390×3520×2790
CI5X1415 Φ1400×1500 1540×1320 900 350-550 250 24 2995×2790×3090
CI5X1620 Φ1600×2000 2040×1630 1100 500-900 2×200 42 3485×3605×3720
CI5X2023 Φ2000×2300 2400×1920 1300 1200-2000 2×500 76 4890×4380×4765
  • Data mining - Wikipedia

    Data mining can unintentionally be misused, and can then produce results which appear to be significant; but which do not actually predict future behavior and cannot be reproduced on a new sample of data and bear little use. Often this results from investigating too many hypotheses and not performing proper statistical hypothesis testing.A simple version of this problem in machine learning is ...

  • Etymology Background Process Research Standards
  • Data Mining Techniques Top 7 Data Mining Techniques

    Statistical Techniques. Data mining techniques statistics is a branch of mathematics which relates
  • What is Data Analysis and Data Mining? - Database Trends ...

    7/01/2011  In all data mining applications, results are considerably subject to interpretation, since it is a search for trends and correlation rather than an examination of hypotheses based on known real-world information. The possibility for spurious results is large, and there are many cases where the information developed will be of little real value ...

  • 作者: Lynn Greiner
  • 1.8: Evaluating Mining Results - Introduction and Data ...

    Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains.

  • 5 data mining techniques for optimal results

    发布日期: 1/04/2011
  • What Is Data Mining? - Oracle Help Center

    ModelsDetailsVariationsOtherCriticismsBenefitsIntroductionActivitiesUsesFormatExampleResultsIssuesSummaryAdvantagesData mining is accomplished by building models. A model uses an algorithm to act on a set of data. The notion of automatic discovery refers to the execution of data mining models. Data mining models can be used to mine the data on which they are built, but most types of models are generalizable to new data. The process of applying a model to new data is known as scoring.
  • Data Mining Result - an overview ScienceDirect Topics

    Data mining result visualization: Visualization of data mining results is the presentation of the results or knowledge obtained from data mining in visual forms. Such forms may include scatter plots and boxplots ( Chapter 2 ), as well as decision trees, association rules,

  • Data Mining Definition - Investopedia

    Data mining is a process used by companies to turn raw data into useful information. By using software to look for patterns in large batches of data, businesses can learn more about their ...

  • Know The Best 7 Difference Between Data Mining Vs Data ...

    While Data mining is based on Mathematical and scientific methods to identify patterns or trends, Data Analysis uses business intelligence and analytics models. Data mining generally doesn’t involve visualization tool, Data Analysis is always accompanied by visualization of results. Data Mining Vs Data Analysis Comparison Table

  • How To Visualize Data Mining Results IT Training and ...

    26/07/2006  An important part of understanding data mining models is the context in which they are connected with your own marketing strategies. Once you are able to visualize the models of a data mining programs, you will next want to interact with the things you visualize so that you are able to answer basic questions.

  • Examples of data mining - Wikipedia

    Additionally, sophisticated applications could be used to automate mailing. Once the results from data mining (potential prospect/customer and channel/offer) are determined, this "sophisticated application" can either automatically send an e-mail or a regular mail.

  • Search results for: data mining - publications.waset.org

    Data mining has been becoming more and more important and a wide range of applications in recent years. Data mining is the process of find hidden and unknown patterns in big data. One of the applied fields of data mining is Customer Relationship Management. Understanding the relationships between products and customers is crucial for every ...

  • 7 Examples of Data Mining - Simplicable

    Data mining is a diverse set of techniques for discovering patterns or knowledge in data.This usually starts with a hypothesis that is given as input to data mining tools that use statistics to discover patterns in data.Such tools typically visualize results with an interface for exploring further. The following are illustrative examples of data mining.

  • 5 real life applications of Data Mining and Business ...

    As the importance of data analytics continues to grow, companies are finding more and more applications for Data Mining and Business Intelligence. Here we take a look at 5 real life applications of these technologies and shed light on the benefits they can bring to your business. Service providers

  • Advantages and Disadvantages of Data Mining - zentut

    Advantages of Data Mining Marketing / Retail. Data mining helps marketing companies build models based on historical data to predict who will respond to the new marketing campaigns such as direct mail, online marketing campaignetc. Through the results, marketers will have an appropriate approach to selling profitable products to targeted ...

  • ch 4 data mining Computer Science Flashcards Quizlet

    d. the process aspect means that data mining should be a one-step process to results. d. the process aspect means that data mining should be a one-step process to results. What is the main reason parallel processing is sometimes used for data mining? Select one: a. because any strategic application requires parallel processing b. because the most of the algorithms used for data mining require ...

  • Visualization Techniques to Explore Data Mining Results ...

    applications, and includes data mining methods based on searching for patterns like frequent sets or association rules. Keyword graphs are used in this system as an highly interactive technique to present the mining results. The user can operate on the visualized results, either to redirect the data mining process, to filter and structure the ...

  • Search results for: Data mining - publications.waset.org

    The analysis can be done by using the concept of Data Mining and the major part are analyzed based on the predictive data mining. The results are predicted from the historical data (past data) and track the relevant solution which is required. Weka tool is used for the analysis of data based on predictive data mining.

  • Data Mining Results - social.msdn.microsoft

    I have been building a Decision Tree predictive model and I have noticed that I create the same mining structure with the same data set and build a model, my results vary. For example, if I build a mining structure and decision tree model, the model may show me that one variable is predictive ... Some parameters of the algorithm are based on random ...

  • The Top 10 Data Mining Tools of 2018 Analytics Insight

    Data mining is the process where the discovery of patterns among large data to transform it into effective information is performed. This technique utilizes specific algorithms, statistical analysis, artificial intelligence and database systems to extract information from

  • 6 essential steps to the data mining process

    Data mining process is the discovery through large data sets of patterns, relationships and insights that guide enterprises measuring and managing where they are and predicting where they will be in the future. First, it is required to understand business objectives clearly and find out what are the

  • (PDF) When do data mining results violate privacy?

    This is because of the overheads that injected by privacy preserving methods in decreasing the accuracy of end results of data mining. Soft computing is a general name of a group of logic based ...

  • View and Save the Results of a Prediction Query ...

    The results are displayed in a grid in the viewer. Save the results of a prediction query to a table. On the toolbar of the Mining Model Prediction tab in Data Mining Designer, click Save query result. The Save Data Mining Query Result dialog box opens. Select a data source from the Data Source list, or click New to create a new data source.

  • Interpreting Data Mining Results with Linked Data for ...

    of data mining and linked data (as promoted for example in [5]), and how such an approach is generally relevant to Learning Analytics. 2. MINING ENROLMENT DATA In order to illustrate the need and general idea for linked data-based interpretation of data mining results, we rely on a concrete scenario: the analysis of student enrolment data.

  • 发布位置:learning analytics and knowledge 2013作者:Mathieu Daquin Nicolas Jay从属关系: Open University University of Lorraine关于:Sequential Pattern Mining Data mining Linked data
  • Data Mining - an overview ScienceDirect Topics

    To get the hidden, previously unknown information from data requires special expertise. Visualization is an integrated component of the data mining process. Data mining results are often communicated to researchers via a convenient, easy-to-perceive visual interface.

  • Football Result Predictions - dataminingsoccer

    Prediction of football results on the basis of statistical analyses of many historical data using a data-mining software.

  • Data Mining Results - social.msdn.microsoft

    I have been building a Decision Tree predictive model and I have noticed that I create the same mining structure with the same data set and build a model, my results vary. For example, if I build a mining structure and decision tree model, the model may show me that one variable is predictive ... Some parameters of the algorithm are based on random ...

  • Retrieve Data from a Data Mining Model (DMX) (SSRS)

    Retrieve Data from a Data Mining Model (DMX) (SSRS) 03/14/2017; 3 minutes to read +1; In this article. To use data from a SQL Server Analysis Services data mining model in your report, you must define a SQL Server Analysis Services data source and one or more report datasets.

  • Top 5 Data Mining Techniques - infogix

    8/09/2015  Each of the following data mining techniques cater to a different business problem and provides a different insight. Knowing the type of business problem that you’re trying to solve, will determine the type of data mining technique that will yield the best results.

  • When do data mining results violate privacy? - Quora

    If data mining is confined to published information then I believe the answer should be “never” but I can see how many people would find this disturbing. I find it disturbing but it is the only rational answer to this question. Everything publicly...

  • Data mining Better Evaluation

    Computerisation allows for the application of complex algorithms to large data sets, enabling results to be generated very quickly at negligible cost. Although data mining algorithms are usually applied to large data sets, some algorithms can also be applied to relatively small data sets. Data sets used in data mining are simple in structure: ...

  • Data Mining SQLIO Results – SQLServerCentral

    This article describes an analysis of SQLIO results using two data mining models in Analysis Services, and Excel to clarify and confirm model conclusions. The SQLIO script suggested here http ...

  • Getting Data Mining results into SQL Tables – Jamie's Junk

    8/10/2008  I’ve been seeing lots of questions about how to get data mining results into SQL tables. Most times the answers are “use the prediction query builder save button” or “build an SSIS package.” Both of these have issues among them being that the former is

  • 4 Important Data Mining Techniques - Data Science

    Data Mining is an important analytic process designed to explore data. Much like the real-life process of mining diamonds or gold from the earth, the most important task in data mining is to extract non-trivial nuggets from large amounts of data.

  • What is data mining? SAS

    Data mining is the process of finding anomalies, patterns and correlations within large data sets to predict outcomes. Using a broad range of techniques, you can use this information to increase revenues, cut costs, improve customer relationships, reduce risks and more. Over the last decade

  • Data Mining: How You're Revealing More Than You Think ...

    12/07/2018  Data mining recently made big news with the Cambridge Analytica scandal, but it is not just for ads and politics. It can help doctors spot fatal infections and it can even predict massacres in the ...

  • 作者: SciShow

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