{"id":7984,"date":"2018-02-13T14:41:58","date_gmt":"2018-02-13T14:41:58","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=7984"},"modified":"2021-05-28T14:05:45","modified_gmt":"2021-05-28T08:35:45","slug":"data-mining-and-knowledge-discovery","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/data-mining-and-knowledge-discovery\/","title":{"rendered":"Data Mining and Knowledge Discovery Database(Kdd Process)"},"content":{"rendered":"<p>In this Article for Data Mining, we will study Data Mining and Knowledge Discovery. Also, will learn Knowledge discovery database and aspects in Data Mining. Further, we will try to cover Issues in data mining, Elements of Data Mining and Knowledge Discovery, and Kdd Process.<\/p>\n<p>So, let&#8217;s start\u00a0Data Mining and Knowledge Discovery Database(Kdd Process).<\/p>\n<div id=\"attachment_49826\" style=\"width: 1210px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Data-analysis.jpg\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-49826\" class=\"wp-image-49826 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Data-analysis.jpg\" alt=\"Data Mining and Knowledge Discovery Database(Kdd Process)\" width=\"1200\" height=\"628\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Data-analysis.jpg 1200w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Data-analysis-150x79.jpg 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Data-analysis-300x157.jpg 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Data-analysis-768x402.jpg 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Data-analysis-1024x536.jpg 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Data-analysis-520x272.jpg 520w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/a><p id=\"caption-attachment-49826\" class=\"wp-caption-text\">Data Mining and Knowledge Discovery Database(Kdd Process)<\/p><\/div>\n<h3 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Data Mining and Knowledge Discovery<\/h3>\n<p class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\"><strong>What is Knowledge Discovery?<\/strong><\/p>\n<p>Some people don\u2019t differentiate <strong>data mining<\/strong> from knowledge discovery. While others view data mining as an essential step <span class=\"complexword\">in the process of<\/span> knowledge discovery. Here is the list of steps involved in the kdd process in data mining \u2212<\/p>\n<p>1. <strong>Data Cleaning<\/strong> \u2212 Basically in this step, the noise and inconsistent data <span class=\"passivevoice\">are removed<\/span>.<\/p>\n<p>2. <strong>Data Integration<\/strong> \u2212 Generally, in this step, <span class=\"complexword\">multiple<\/span> data sources <span class=\"passivevoice\">are combined<\/span>.<\/p>\n<p>3.<strong> Data Selection<\/strong> \u2212 Basically, in this step, data relevant to the analysis task <span class=\"passivevoice\">are retrieved<\/span> from the database.<\/p>\n<p>4. <strong>Data Transformation<\/strong> \u2212In this step, data <span class=\"passivevoice\">is transformed<\/span> into forms appropriate for mining. Also, by performing summary or aggregation operations.<\/p>\n<p>5. <strong>Data Mining<\/strong> \u2212 Generally, In this, intelligent methods <span class=\"passivevoice\">are applied<\/span> <span class=\"complexword\">in order to<\/span> extract data patterns.<\/p>\n<p>6. <strong>Pattern Evaluation<\/strong> \u2212 Basically in this step, data patterns <span class=\"passivevoice\">are evaluated<\/span>.<\/p>\n<p>7. <strong>Knowledge Presentation<\/strong> \u2212 Generally, in this step, knowledge <span class=\"passivevoice\">is represented<\/span>.<\/p>\n<h3 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Knowledge Discovery Database In Data Mining<\/h3>\n<p>The process of finding and interpreting patterns\u00a0from data involves the repeated application of the following steps:<\/p>\n<p><strong>Developing an understanding of:<\/strong><\/p>\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">The application domain<\/li>\n<\/ul>\n<ul>\n<li>Relevant prior knowledge<\/li>\n<\/ul>\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">The goals of the end-user<\/li>\n<\/ul>\n<p><strong>Creating a target dataset:<\/strong><\/p>\n<p>Selecting a data set, or focusing on a subset of variables, or data samples, on which discovery is to <span class=\"passivevoice\">be performed<\/span>.<\/p>\n<p><strong>Data cleaning and preprocessing:<\/strong><\/p>\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Removal of noise or outliers.<\/li>\n<\/ul>\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Collecting necessary information to model or account for noise.<\/li>\n<\/ul>\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Strategies for handling missing data fields.<\/li>\n<\/ul>\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Accounting for time sequence information and known changes.<\/li>\n<\/ul>\n<p><strong>Data reduction and projection:<\/strong><\/p>\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Finding useful features to represent the data depending on the goal of the task.<\/li>\n<\/ul>\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Using dimensionality reduction methods to reduce the effective number of variables. That is under consideration or to find invariant representations for the data.<\/li>\n<\/ul>\n<p><strong>Choosing the data mining task:<\/strong><\/p>\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Deciding whether the goal of the KDD process is <strong>classification<\/strong>, regression, <strong>clustering<\/strong>, etc.<\/li>\n<\/ul>\n<p><strong>Choosing the data mining algorithm(s):<\/strong><\/p>\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Selecting method(s) to <span class=\"passivevoice\">be used<\/span> for searching for patterns in the data.<\/li>\n<\/ul>\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Deciding which models and parameters may be appropriate.<\/li>\n<\/ul>\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Matching a particular data mining method with the criteria of the KDD process.<\/li>\n<\/ul>\n<p><strong>Data Mining:<\/strong><\/p>\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Searching for patterns of interest in a particular representational form. Such representations as classification rules or trees, regression, clustering, and so forth.<\/li>\n<\/ul>\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Interpreting mined patterns.<\/li>\n<\/ul>\n<ul>\n<li class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Consolidating discovered knowledge.<strong>\u00a0<\/strong><\/li>\n<\/ul>\n<h3 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Aspects Of Data Mining<\/h3>\n<div id=\"attachment_8377\" style=\"width: 1090px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Process-01-1.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-8377\" class=\"wp-image-8377 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Process-01-1.png\" alt=\"Aspects of Data Mining and Knowledge Discovery\" width=\"1080\" height=\"1080\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Process-01-1.png 1080w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Process-01-1-150x150.png 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Process-01-1-300x300.png 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Process-01-1-768x768.png 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Process-01-1-1024x1024.png 1024w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Process-01-1-100x100.png 100w\" sizes=\"auto, (max-width: 1080px) 100vw, 1080px\" \/><\/a><p id=\"caption-attachment-8377\" class=\"wp-caption-text\">Aspects of Data Mining and Knowledge Discovery<\/p><\/div>\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">a. Data Integration<\/h4>\n<p>First of all the data <span class=\"passivevoice\">is collected<\/span> and integrated from all the different sources.<\/p>\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">b. Data Selection<\/h4>\n<p>Generally, we may not all the data we have collected in the first step. Also, in this step, we select only those data which <span class=\"qualifier\">we think<\/span> useful for data mining.<\/p>\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">c. Data Cleaning<\/h4>\n<p>Generally, the data we have collected is not clean and may contain errors, missing values, noisy or inconsistent data. <span class=\"complexword\">Therefore<\/span> we need to apply different techniques to get rid of such anomalies.<\/p>\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">d. Data Transformation<\/h4>\n<p>Basically, the data even after cleaning is not ready for mining. Also, we need to transform them into forms appropriate for mining. Thus, the techniques used to do this are smoothing, aggregation, normalization etc.<\/p>\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">e. Data Mining<\/h4>\n<p>As now in this step, we are ready to apply <strong>data mining techniques<\/strong> on the data. Basically, it is to discover the interesting patterns. Hence, clustering and association analysis are among the many different techniques present. Also, as we used for data mining.<\/p>\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">f. Pattern Evaluation and Knowledge Presentation<\/h4>\n<p>Generally, this step includes visualization, transformation, removing redundant patterns from the patterns we generated.<\/p>\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">g. Decisions \/ Use of Discovered Knowledge<\/h4>\n<p>As this step is beneficial to us. Also, it helps to use the knowledge acquired to take better decisions.<\/p>\n<h3 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Issues In Data Mining<\/h3>\n<p><span class=\"complexword\">I<\/span>ssues that need to <span class=\"passivevoice\">be addressed by<\/span> any serious data mining package are:<\/p>\n<p>i. Uncertainty Handling<\/p>\n<p>ii. Dealing with Missing Values<\/p>\n<p>ii. Dealing with Noisy data<\/p>\n<p>iv. The efficiency of algorithms<\/p>\n<p>v. Constraining Knowledge Discovered to only Useful<\/p>\n<p>vi. Incorporating Domain Knowledge<\/p>\n<p>vii. Size and Complexity of Data<\/p>\n<p>viii. Data Selection<\/p>\n<p>ix. Understandability of Discovered Knowledge: Consistency between Data and Discovered Knowledge<\/p>\n<h3 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Five Major Elements of Data Mining<\/h3>\n<div id=\"attachment_8378\" style=\"width: 1210px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Process-02.png\"><img loading=\"lazy\" decoding=\"async\" aria-describedby=\"caption-attachment-8378\" class=\"wp-image-8378 size-full\" src=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Process-02.png\" alt=\"Elements of Data Mining and Knowledge Discovery\" width=\"1200\" height=\"628\" srcset=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Process-02.png 1200w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Process-02-150x79.png 150w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Process-02-300x157.png 300w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Process-02-768x402.png 768w, https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Process-02-1024x536.png 1024w\" sizes=\"auto, (max-width: 1200px) 100vw, 1200px\" \/><\/a><p id=\"caption-attachment-8378\" class=\"wp-caption-text\">Elements of Data Mining and Knowledge Discovery<\/p><\/div>\n<p>i. Extract, transform and load transaction data onto the data warehouse system.<\/p>\n<p>ii. Basically, it stores and manages the data in a multidimensional database system.<\/p>\n<p>iii. Generally, provide data access to business analysts and information technology professionals.<\/p>\n<p>iv. As basically it analyzes the data by application software.<\/p>\n<p>v. Basically, it shows the data in a useful format, such as a graph or table.<\/p>\n<h3 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Levels Of Analysis in Data Mining<\/h3>\n<p>Following are levels of analysis in Data Mining And Knowledge Discovery Databases.<\/p>\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">a. Artificial Neural Networks<\/h4>\n<p>Basically, there are present non-linear predictive models. That learn through training and resemble biological neural networks in structure.<\/p>\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">b. Genetic Algorithms<\/h4>\n<p>Generally, there are optimization techniques that use this process. Such as genetic combination, mutation. Also, natural selection in a design based on the concepts of natural evolution.<\/p>\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">c. Nearest Neighbor Method<\/h4>\n<p>Basically, it is a technique that classifies each record in a dataset. Also, as it <span class=\"passivevoice\">is based<\/span> on a combination of the classes of the k record(s) most <span class=\"complexword\">similar to<\/span> it in a historical data set.<\/p>\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">d. Rule Induction<\/h4>\n<p>Generally, the extraction of useful if-then rules from data based on statistical significance.<\/p>\n<h4 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">e. Data Visualization<\/h4>\n<p>Basically, the visual interpretation of complex relationships in multidimensional data. Also, we use graphics tools to illustrate data relationships.<\/p>\n<h3 class=\"public-DraftStyleDefault-block public-DraftStyleDefault-ltr\">Conclusion<\/h3>\n<p>As a result, we have studied Data Mining and Knowledge Discovery. Also, learned Aspects of Data Mining and knowledge discovery, Issues in data mining, Elements of Data Mining and Knowledge Discovery, and Kdd Process. etc. As this, all should help you to understand Knowledge Discovery in Data Mining. Furthermore, if you have any query, feel free to ask in a comment section.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this Article for Data Mining, we will study Data Mining and Knowledge Discovery. Also, will learn Knowledge discovery database and aspects in Data Mining. Further, we will try to cover Issues in data&#46;&#46;&#46;<\/p>\n","protected":false},"author":6,"featured_media":49826,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[18],"tags":[1162,3499,3906,3970,5064,7330,7989,7990,7991,7992,9021,15808],"class_list":["post-7984","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-mining","tag-artificial-neural-networks","tag-data-visualization","tag-different-levels-of-analysis","tag-discovery-databases","tag-genetic-algorithms","tag-issues-in-data-mining","tag-kdd-data-mining","tag-kdd-process","tag-kdd-process-in-data-mining","tag-kdd-process-overview","tag-nearest-neighbor-method","tag-what-is-knowledge-discovery"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Data Mining and Knowledge Discovery Database(Kdd Process) - DataFlair<\/title>\n<meta name=\"description\" content=\"Data Mining and Knowledge Discovery - Data MiningKdd process, Aspects Of Data Mining, Issues in Data Mining, Level of Analysis &amp; Elements of Data Mining\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/data-mining-and-knowledge-discovery\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Data Mining and Knowledge Discovery Database(Kdd Process) - DataFlair\" \/>\n<meta property=\"og:description\" content=\"Data Mining and Knowledge Discovery - Data MiningKdd process, Aspects Of Data Mining, Issues in Data Mining, Level of Analysis &amp; Elements of Data Mining\" \/>\n<meta property=\"og:url\" content=\"https:\/\/data-flair.training\/blogs\/data-mining-and-knowledge-discovery\/\" \/>\n<meta property=\"og:site_name\" content=\"DataFlair\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/DataFlairWS\/\" \/>\n<meta property=\"article:published_time\" content=\"2018-02-13T14:41:58+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2021-05-28T08:35:45+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/data-flair.training\/blogs\/wp-content\/uploads\/sites\/2\/2018\/02\/Data-analysis.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"628\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"DataFlair Team\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:site\" content=\"@DataFlairWS\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"DataFlair Team\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"6 minutes\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Data Mining and Knowledge Discovery Database(Kdd Process) - 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