data mining with rattle and r

]} = \frac{|x_{if}-x_{jf}|} {\max_{h} x_{hf}-\min_{h} X_{HF} $, where h passes all non-missing objects of property F. F is nominal or two yuan: if \ (x_{if} = x{jf}\), then \ (d_{ij}^{[f]}=0\), otherwise take 1. F is ordinal: computes the rank \ (r_{if}\) and \ (z_{if} = \frac{r_{if}-1}{m_f-1}\)and then processes it as a numeric attribute. Cosine similarityTo compare documents, each document is represented by a so-called word frequency vector, usually very long and sparse, and the t

Data analysis and miningBaidu MTC is an industry-leading mobile application testing service platform, providing solutions for the costs, technologies, and efficiency problems faced by developers in mobile application testing. At the same time, we will share the industry's leading Baidu technology, written by Baidu employees and industry leaders.1. Overview 1.1 the key to the success of a mobile app is marketing and product design, the core of

Label: What exactly is data mining? obviously data mining is not magic,Data Mining is the use of complex mathematical algorithms, so that we can use the computer's powerful computing power to sift through a large number of detai

Because data mining can bring significant economic benefits, it is widely used in electronic commerce, especially in finance, retailing and telecom industry. In the financial field, managers can classify and rank by analyzing the customer's ability to repay and credit. This can reduce the numbness of lending and improve the efficiency of the use of funds. It can also be found that the leading factor in the

With the advent of the cloud era and the introduction of SAAS concepts, more and more enterprises are choosing to provide SaaS application services through Internet platforms such as SaaS application providers and carriers, the data volume of SAAS applications is growing at the TB level. Different SaaS application systems provide different data structures, including text, graphics, and even small databases;

enterprises. With the rapid development of computer technology, network technology, communication technology, and Internet technology and the popularization of e-commerce, office automation, management information systems, and Internet, business operation processes of enterprises are increasingly automated, A large amount of data is generated during the enterprise's operation. These data and the resulting

0 S T S + T Sum Q + S R + T P = q + S + T + R Now let's look at the similarity: Q and T. That is, similarity measurement: d (I, j) = (q + T)/P = (q + T)/(q + S + T + r) Conversely, the opposite sex is a different measurement value .. That is, S and R, D (I, j) = (S + r)/P Of course, what we calculate is symmetric binary. What is a symmetric Binary Attribute? Both are meaningful and important in reality. Next, asymmetric binary similarity is assumed

independent and has no correlation.If that is less than 0, the description is negatively correlated, and one value increases by another.Note that correlations do not imply causality, and if A and B are relevant, it does not mean that a causes B or B to cause a.3. Covariance of numeric dataCovariance and variance are two similar measures that evaluate how the two properties change together. The mean values of A and B are also known as expectations.The covariance of A and B is defined as:　　　　For

ObjectiveThis article continues our Microsoft Mining Series algorithm Summary, the previous articles have been related to the main algorithm to do a detailed introduction, I for the convenience of display, specially organized a directory outline: Big Data era: Easy to learn Microsoft Data Mining algorithm summary seria

) barplot (table (data))2.3Data $, the, -, the, the, -) Median2sum=0 for(Iinch 1: Length (data)) {Sum=sum+Data[i]if(sum1]>median) Break} #出循环后i+1 is the subscript of the median interval, i.e. 20~ - -+ (sum (data)/2+sum)/data[i+1])* -2.4Age at, at, -, -, the, A, -, the, -, th

Common Data Mining MethodsBasic Concepts Data Mining is fromMassive, incomplete, noisy, and fuzzyThe process of extracting potentially useful information and knowledge hidden in the data that people do not know beforehand. Specifically, as a broad application-oriented cross-

What is http://www.quora.com/What-is-data-science data science?Http://www.quora.com/How-do-I-become-a-data-scientist how can I become a data scientist?Http://www.quora.com/Data-Science/How-does-data-science-differ-from-traditional

In various data mining algorithms, association rule mining is an important one, especially influenced by basket analysis. association rules are applied to many real businesses, this article makes a small Summary of association rule mining. First, like clustering algorithms, association rule