Outliers In Data Mining

Data mining is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data preprocessing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. B.2 Introduction The growing popularity and development of data mining technologies bring serious threat to the security of individual's

Qualitative Data Analysis Scholars and analysts have numerous strategies for conducting research. Various methods have different advantages and disadvantages that researchers consider before identifying the most appropriate design. While there are multiple ways of implementing research, quantitative and qualitative methods are arguably the most famous strategies for analysis. This webinar concentrates on qualitative data analysis and sheds light on various aspects including the meaning of qualitative data, the meaning of analysis, the most difficult stages of qualitative research, the major characteristics of analysis process, when data analysis should start and end, the major steps in data analysis and the crucial issues that may

We can view a probability distribution in two ways. The basic view is the Probability function, which specifies the probability that the random variable takes on a specific value: P(X=x) is the probability that a random variable X takes on a specific value x. (Note that capital X represents the random variable and lowercase x represents a specific value that the random variable may take). For a discrete random variable, the shorthand notation for the probability function is p(x) = P (X=x). For continuous random variables, the probability function is denoted f(x) and called the probability density function.

To handle such concerns, numerous data security-enhancing techniques have been developed. In addition, there has been a great deal of recent eort on develop- ing privacy-preserving data mining methods. In this section, we look at some of the advances in protecting privacy and data security in data mining. What can we do to secure the privacy of individuals while collecting and mining data?" Many data se-

The CWT can be expressed as Inverse Continuous Wavelet Transform: CWT is highly redundant since 1-dimensional function x(t) is transformed into 2-dimensional function. Therefore, it is discretize to some suitably chosen sample grid. The is called as dyadic sampling: s=2-j, τ = k2-j. By using the dyadic sampling we can reconstruct exactly the signal

A. Group Assignment a. Discuss the two data mining methodologies The process of going through massive sets of data looking out for unsuspected patterns which can provide us with advantageous information is known as data mining. With data mining, it is more than possible or helping us predict future events or even group populations of people into similar characteristics. Cross Industry Standard Process for Data Mining (CRISP-DM) is a 6-phase model of the entire data mining process which is commonly used across industries for a wide array of data mining projects and provides a structured approach to planning a data mining project. The 6 phases are: Business Understanding – Focuses and understand what the project objectives, requirements

We must consider the time, location validity and form of the information. Information flows out from the top to bottom and bottom to top. However, sometimes information makes problems where there is too much information and one might make a mistake. For example, when you search a subject on internet, you find too much information that makes you confused on which one to use and wonder if it is right. People must use information in order to finish their work.

This hypothesis testing uses the test statistics in which mechanism is based on the correlation integrals. The BDS test is a powerful tool for detecting serial dependence in time series. It tests the null hypothesis of independent and identically distributed (I.I.D.) against an unspecified alternative. The null and alternative hypothesis is as follows: H0: The data are independently and identically distributed (I.I.D.).

These forensic tools are playing an important role in the law enforcement. They helps in password identification, log-ons and other important information that are obtained from memory. Evidence preservation The evidences in computer can get easily changed or altered. So the instructors should make or preserve the evidences by making a bit stream copies of the media containing evidences.

Image Steganography Techniques – A Survey Roshni B. Solanki PG student,Computer Engineering Sarvajanik College of Engineering Technology Surat, India roshanisolanki23@gmail.com Abstract— In today’s era, due to advancements in the field of information technology, the need for information security is highly increasing day by day. Steganography plays a major role in secret data communication. It is nothing but to communicate in such a way that not only the contents are hidden but also the existence of message is kept secret which makes it different from cryptography which concerns only with keeping the contents secret. Steganography can be accomplished by hiding the information in other information, and for that, many different carrier file

where $x_i,i=1,2, cdots ,n$ are the states, $underline{x}_i=[x_1,cdots,x_i]^{T} in{R}^i$, $i=1,2, cdots ,n $, $uin {R}$ is the input, and $f_i(cdot)$,$i=1,2, cdots ,n $ are the unknown smooth nonlinear functions which satisfy the global Lipschitz condition. It is assumed that the output $y(cdot)$ is sampled at instants $t_k,k=1,2, cdots ,n$, which represent the sampling instants. $T=t_{k+1}-t_k$ is the sampling interval which is a positive constant. The output signal is available for the observer at instants $t_k+ au_k$, where $ au_k$ are the transmission delays and satisfy $0 leqslant au_k leqslant T$. egin{remark} label{rem:1}

There are many archetypes in the literature that attracts both readers and audiences. These archetypes make the scene more dramatic by using the typical situation, symbol, and character type. But specifically, the characteristic of the outcast appears in many animation movies and fictions. The movie ‘Beauty and the Beast’ is a story of Bell who went to save her father who was trapped in the beast’s castle but eventually fell in love with the beast. The effect of the outcast who is banished from a community in the movies is that audiences no more think that outcasts like beasts are always bad and abandoned, and the purpose of his archetype is to break down stereotype.