classification and prediction in data mining pdf

Classification and prediction in data mining pdf

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A Sample Classification Problem

A Sample Classification Problem

About Classification


The greatest challenge in front of every data scientist is making this raw data, a meaningful one to solve a business problem. Data is the beginning point of all data mining process. The raw data or the collected data cannot use directly to build the business models.

A Sample Classification Problem

There are two forms of data analysis that can be used for extracting models describing important classes or to predict future data trends. Classification models predict categorical class labels; and prediction models predict continuous valued functions. For example, we can build a classification model to categorize bank loan applications as either safe or risky, or a prediction model to predict the expenditures in dollars of potential customers on computer equipment given their income and occupation. A bank loan officer wants to analyze the data in order to know which customer loan applicant are risky or which are safe. A marketing manager at a company needs to analyze a customer with a given profile, who will buy a new computer.


A Sample Classification Problem

Data mining is a process of extracting and discovering patterns in large data sets involving methods at the intersection of machine learning , statistics , and database systems. The term "data mining" is a misnomer , because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction mining of data itself. The book Data mining: Practical machine learning tools and techniques with Java [8] which covers mostly machine learning material was originally to be named just Practical machine learning , and the term data mining was only added for marketing reasons. The actual data mining task is the semi-automatic or automatic analysis of large quantities of data to extract previously unknown, interesting patterns such as groups of data records cluster analysis , unusual records anomaly detection , and dependencies association rule mining , sequential pattern mining. This usually involves using database techniques such as spatial indices. These patterns can then be seen as a kind of summary of the input data, and may be used in further analysis or, for example, in machine learning and predictive analytics.

Crime prediction uses past data and after analyzing data, predict the future crime with location and time. In First. Crime analysis and prevention is a systematic approach for identifying and analyzing patterns and trends in crime. Querying can be done in a familiar style with a derive statement that can be used like a select This paper presents a methodology of analysis of crime facts from online newspapers, identifying the different communes where the greatest number of criminal events occur, which gives an idea of potentially more dangerous places, through the detection and geographical mapping of critical points, or the analysis of the nature of the crime through the extraction of entities. Initially, their function was devised to assist in complex murder cases with unknown offender.

In talent management, process to identify a potential talent is among the crucial tasks and need highly attentions from human resource professionals. Nowadays, data mining DM classification and prediction techniques are widely used in various fields. However, this approach has not attracted much interest from people in human resource. In this article, we attempt to determine the potential classification techniques for academic talent forecasting in higher education institutions. Academic talents are considered as valuable human capital which is the required talents can be classified by using past experience knowledge discovered from related databases. As a result, the classification model will be used for academic talent forecasting.

About Classification

Predictive Analytics is a progressive and excellent area of data analytics which guess some event, appearance or likelihood dependent on existing information. Predictive Analytics utilizes data mining methods with the goal to make forecasts about future occasions, and make proposals dependent on these expectations. The procedure includes an investigation of memorable information and dependent on that examination to foresee the future events or occasions. Presently a-days Predictive Analytics is the essential idea in the Mining of educational data.


What is prediction?

 - Абсолютно. Скажи папе, что все в порядке. Но нутром он чувствовал, что это далеко не. Интуиция подсказывала ему, что в глубинах дешифровального чудовища происходит что-то необычное. ГЛАВА 10 - Энсей Танкадо мертв? - Сьюзан почувствовала подступившую к горлу тошноту.  - Вы его убили. Вы же сказали… - Мы к нему пальцем не притронулись, - успокоил ее Стратмор.

Data Mining - Classification & Prediction



  • Josh B. 18.04.2021 at 01:30

    This chapter describes classification, the supervised mining function for predicting a categorical target.

  • Mandel R. 20.04.2021 at 11:55

    Finite math and applied calculus pdf whole-genome random sequencing and assembly of haemophilus influenzae rd pdf

  • Marko W. 24.04.2021 at 01:57

    Data Mining Concepts and Techniques (2nd Edition). Jiawei Han and Other classification methods. ▫. Prediction. ▫. Accuracy and error measures. ▫.


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