DATA MINING TECHNIQUES

Institution UNIVERSITY
Course FORENSICS
Year 1st Year
Semester Unknown
Posted By Brian Mike
File Type pdf
Pages 21 Pages
File Size 545.18 KB
Views 5169
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Description

The paper presents application of data mining techniques to fraud analysis. We present some classification and prediction data mining techniques which we consider important to handle fraud detection. There exist a number of data mining algorithms and we present statistics-based algorithm, decision treebased algorithm and rule-based algorithm. We present Bayesian classification model to detect fraud in automobile insurance. Naïve Bayesian visualization is selected to analyze and interpret the classifier predictions. We illustrate how ROC curves can be deployed for model assessment in order to provide a more intuitive analysis of the models
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LESSON 4: MEASURES OF DISPERSION Trending!
The measures of central tendency are not sufficient measures to reveal the shape of the distribution of data set. The measures that show the spread of a data set are called the measures of dispersion. The main measures of dispersion are range, inter quartile range, standard deviation, variance and coefficient of variation. In this lesson we will discuss these measures of dispersion.
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7 Pages 7995 Views 0 Downloads 152.45 KB
LESSON 2: MEASURES OF CENTRAL TENDENCY Trending!
One of main objectives of statistical analysis is to obtain one single value that describes the characteristic of the entire mass of unwieldy data. Such a value is called the central value or average value. In this lesson we will consider some of central values which are commonly used.
8 Pages 6085 Views 0 Downloads 213.46 KB
LESSON 3: MEASURES OF CENTRAL TENDENCY cont.. Trending!
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10 Pages 6867 Views 0 Downloads 246.31 KB
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SZL 105: LABORATORY METHODS AND TECHNIQUES IN ZOOLOGY Trending!
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31 Pages 8239 Views 11 Downloads 681.05 KB
SST 305: Theory of Estimation Notes Trending!
The objective of statistics is to make an inference about a population based on information contained in a sample. Most statistical inference procedures involve either estimation or hypothesis testing. This course looks at estimation.
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SMA 335: Ordinary Differential Equation 1 Trending!
The subject of differential equations constitutes a very important and useful branch of modern m mathematics. In this lesson we sh all consider some definition of ordinary differential equations.
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LESSON 7: REGRESSION AND CORRELATION ANALYSIS Trending!
In this lesson we will discuss regression and correlation. Correlation analysis deals with the association between two or more variables; while regression analysis attempts to establish the nature of the relationship between variables.
11 Pages 5630 Views 1 Downloads 271.03 KB
LESSON 6: SKEWNESS AND KURTOSIS Trending!
Skewness refers to lack of symmetry. A skewed distribution is a frequency distribution that is asymmetric (not symmetric). When the longer tail of a distribution extends to the right, it is said to be skewed to the right and when the longer tail of a distribution extends to the left, it said to be skewed to the left.
9 Pages 6038 Views 0 Downloads 257.5 KB