IT433 Data Warehousing and Data Mining — Data Preprocessing — 1 Data Preprocessing • Why preprocess the data? • Descriptive data summarization • Data cleaning • Data integration and transformation • Data reduction • Discretization and concept hierarchy generation • Summary 2 Why Data Preprocessing? • Data in the real world is dirty – incomplete: lacking attribute values‚ lacking certain attributes of interest‚ or containing only aggregate data • e.g.‚ occupation=“ ”
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Solubility Curve of Sodium Nitrate Data collection |Temperature (°C) | |Mass of solute in 5ml (g) |Mass of solute in 100ml (g) | |1st set of data |2nd set of data |Average | | | |23.5 |24.0 |23.8 |4.5
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Experiment 9: Growth curve of Serratia marcescens Abstract Bacteria grows by binary fission. The aim of this experiment is to follow the growth of Serratia marcescens in nutrient broth at 37oCby recording the changes in turbidity (cloudiness) by measuring the absorbance of visible light (600 nm) and also to prove that there is an increase in the cell number and not just in mass during the growth. In the experiment we measure the full growth curve of Serratia marcescens by measuring the absorbance
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measures widely used to measure complexity in manufacturing systems. With reference to this second framework‚ two indexes were selected (static and dynamic complexity index) and a Business Dynamic model was developed. This model was used with empirical data collected in a job shop manufacturing system in order to test the usefulness and validity of the dynamic complex index. The Business Dynamic model analyzed the trend of the index in function of different inputs in a selected work center. The results
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| Chemistry Lab Report | Constructing Heating/Cooling Curve | | Salman Ishaq 12-E | 1/27/2013 | | BACKGROUND As energy flows from a liquid‚ its temperature drops. The entropy‚ or random ordering of its particles‚ also decreases until a specific ordering of the particles results in a phase change to a solid. If energy is being released or absorbed by a substance remaining at the same temperature‚ this is evidence that a dramatic change in entropy‚ such as a phase change‚ is occurring. Because
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insight into the usage of data warehousing and data mining techniques to enhance the productivity of the business. The study of the processes is analysed so as to get the need of adaptation according to inherent demands of these industries in near future. The main topics we are discussing here are: a) Data warehousing b) Data Mining c) ETL d) Data Mart An attempt has been made to analyse different ways of using these for the enhancement in the different field. Data warehousing and current
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WORLD DATA CLUSTERING ADEWALE .O . MAKO DATA MINING INTRODUCTION: Data mining is the analysis step of knowledge discovery in databases or a field at the intersection of computer science and statistics. It is also the analysis of large observational datasets to find unsuspected relationships. This definition refers to observational data as opposed to experimental data. Data mining typically deals with data that has already been collected for some purpose or the other than the data mining
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effect on the demand curve Markets in Action Advertising and its effect on the demand curve Advertisement has always been an important market strategy for firms to accomplish their goals. From cereal companies to airline companies‚ it is inevitable to go through the process of advertising. However‚ what purpose does advertising serve for consumers and suppliers in the market? In this report‚ it is to examine the relationship between advertising and the market demand curve. Moreover‚ the impact
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Primary Data is Original data‚ this means that it has been collected by you‚ someone who has volunteered to assist you in your research‚ or by someone who is within your employ to gather this research‚ this does not include comparing results with your peers to help evaluate the accuracy of your own results‚ as this type of data has not been gathered by you‚ or have you had any part in the gathering of this information. There are a few ways in which primary data can be obtained‚ which includes surveys
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Censored data & Truncated data Censoring occurs when an observation or a measurement is outside the range and people don’ t know the certain value. The value is always above or below the range that people set. However‚ truncated data means that because of the limits‚ such as time‚ or space‚ people lose some data. Truncation is to cut off the data. In other words‚ we have collected and use the data‚ but the data is not in the range we have. It is called censored data. We don’t use the data because
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